Understanding Behavioral and Physiological Changes Associated with Repetitive Lifting and Vibration Exposure

Understanding Behavioral and Physiological Changes associated with Repetitive Lifting and Vibration Exposure

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Jay Paresh Mehta

Graduate Program in Industrial and Systems Engineering

The Ohio State University

2013

Dissertation Committee:

Steven A. Lavender, Advisor

Carolyn M. Sommerich

Richard J. Jagacinski

Jay Paresh Mehta

2013

Abstract

Repetitive manual lifting and whole body vibration (WBV) exposure encountered in manual handling and delivery type jobs lead to muscle fatigue and are documented risk factors for low back disorder (LBD). The increased rate of muscle fatigue with WBV exposure in delivery occupations is thought to increase the rate of fatigue development during the lifting components of these jobs. In order to compensate for muscle fatigue, people in these occupations may adapt their working strategy to prevent an injury, however, little is known about these adaptive strategies and their effects on LBD risk.

Hence, the goal of this dissertation research was to identify the interactive effects of

WBV and repetitive lifting exposures on muscle fatigue and changes in lifting mechanics.

Study 1 investigated the effects of prolonged repetitive asymmetric lifting task on behavioral adaptations, measures of tissue oxygenation, and spine kinematics during a controlled flexion-extension motion task. Seventeen healthy volunteers repeatedly lifted a box (normalized to 15% of the participant’s lifting capacity) positioned in front of them at ankle level to a location on their left side at waist level at the rate of 10 lifts/minute for a period of 60 minutes. The results showed that this prolonged asymmetric lifting task lead to the development of muscle fatigue observed as a decrease in tissue oxygenation measures (objective) and an increase in the level of perceived exertion (subjective) over

ii time. Behavioral changes with repetitive lifting task included an increase in forward bending motions and velocities in the sagittal and coronal plane. Additionally, the overall lift duration and lateral bending moment of the spine decreased with the repetitive lifting task. Further, significant correlations between muscle physiology measures and changes in spine kinematics and moment measures suggest these behavioral strategies were associated with the development of muscle fatigue. Behavioral measures that increased over time have also been documented to increase the risk of back injury.

Study 2 investigated the interactive effects of seated vibration exposure and lifting task precision demands on behavioral and physiological changes experienced during a repetitive lifting task. This study was a 2 x 2 repeated measures design with two levels of vibration exposure (WBV and no-WBV) and two levels of lifting task precision demands

(High and Low). The initial analyses from study 2 showed no significant interaction between WBV exposure and task precision demands during the repetitive lifting task.

Thus, the data was separately analyzed in study 2a and 2b to understand changes in the physiological and behavioral responses associated with each of these physical factors.

Study 2a focused on the changes in the physiological and behavioral responses to repetitive asymmetric lifting activity after seated exposure to a 5 Hz sinusoidal WBV for one-hour. Seventeen healthy individuals performed the same repetitive asymmetric lifting task as used in study 1 during two experimental sessions. However, prior to initiating the lifting, the participants were seated on a vibrating platform for 60 minutes. In one of the two sessions the platform did not vibrate. The changes in muscle physiology and behavioral measures observed over the 60 minute sessions replicated the findings from

iii study 1. Following exposure to WBV, participants twisted more and did so at a higher movement velocity as they performed the lifting task. In addition to the changes in the magnitude of these responses, the variability (standard deviations) in the lateral bending moment and extension velocity of the spine increased during the lifting that followed

WBV exposure. While the increased variability may suggest compensatory mechanisms to prolong the fatigue development process, the larger spine kinematic and moment response indicated these changes would increase the risk of back injury.

Study 2b focused on the effect of task precision demands during a repetitive asymmetric lifting task on muscle physiology and behavioral measures. Seventeen healthy individuals performed the repetitive lifting task for 60 minutes where the task precision demands on the lifting task were varied by changing the width of the destination conveyor. High precision demands resulted in significantly higher movement times that were largely due to significantly longer placement periods. With high task precision demands, larger sustained twisting motions and lateral bending moments on the spine were observed when placing the box on the conveyor. These behavioral changes suggest that the risk to low back injury is elevated while performing a repetitive asymmetric lifting activity under high task precision demands.

In summary, this research has shown that the risk of low back injury while performing a fatiguing repetitive asymmetric lifting activity is likely due to changes in the adopted behavior. Specifically, the increase in spine laxity, along with a shift towards ballistic movement behavior may increase spinal loading, strains on specific tissues, and thereby increase the risk of injury. Moreover, this risk is further elevated when people are

iv exposed to WBV prior to lifting, and when the lifting requires the object be placed in precise location at its destination.

Dedication

This document is dedicated to my grandparents.

Acknowledgments

This dissertation research would not have been possible without the guidance I received from my advisor and committee members, support from colleagues, friends and family. I would like to take this opportunity to thank several people that have been an integral part of this journey.

I would like to sincerely thank my advisor Dr. Steven A. Lavender for his patience, and providing me with an excellent environment for conducting research. This dissertation could not have been completed without his continual guidance, support and motivation that he provided throughout the years.

I would like to express my sincere gratitude to my committee members Dr.

Carolyn M. Sommerich and Dr. Richard J. Jagacinski for their constant feedback, criticism and advice they provided throughout the completion of this research.

I am grateful to Dr. Sue Ferguson for being available and providing her expertise on the Near-Infrared Spectroscopy system.

I am thankful to Joshua Hassenzahl for his input and assistance in designing the conveyor system and mount for the vibration chair assembly.

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I believe labmates are work family and I would like to thank Sanghyun Park and

Radin Zaid Radin Umar for their assistance in collecting data for pilot work and more importantly being there in my academic highs and lows.

Finally, I would like to thank my family and friends for their love, support and understanding during the long years of my education and always setting higher goals for me to strive for the better.

viii

Vita

2002-2006…………………………………………...... Bachelor of Engineering,

Biomedical Engineering,

Mumbai University

2006-2008…………………………………………...... Master of Science,

Biomedical Engineering,

Marquette University

2009-Present…………………………………………...Graduate Research Associate,

Integrated Systems Engineering,

The Ohio State University

Publications

Mehta, J.P., Kim, T., Lavender, S.A. (2013). Effects of transfer distance on spine kinematics for de-palletizing tasks. Journal of Occupational & Environmental Hygiene, (accepted for publication).

Lavender, S.A., Hedman, G.E., Mehta, J.P., Reichelt, P.A., Conrad, K.M., Park, S. (2013). Evaluating the Physical Demands on Firefighters Using Hand-Carried Stair Descent Devices to Evacuate Mobility-Limited Occupants from High-Rise Buildings. Applied Ergonomics (in press). ix

Lavender, S. A., Mehta, J. P., & Allread, W. G. (2013). Comparisons of tibial accelerations when walking on a wood composite vs. a concrete mezzanine surface. Applied Ergonomics, 44 (5), 824-827.

Sommerich, Carolyn M., Steven A. Lavender, Radin Zaid Radin Umar, Peter Le, Jay Mehta, Pei-Ling Ko, Rafael Farfan, Mohini Dutt, and SangHyun Park. (2012). A biomechanical and subjective assessment and comparison of three ambulance cot design configurations. Ergonomics, 55 (11), 1350-1361.

Mehta, J, Verber, M., Wieser, J, Schmit, B., Schindler-Ivens, S. (2012). The Effect of Movement Rate and Complexity on Functional Magnetic Resonance Signal Change during Pedaling. Motor Control, 16, 158-175.

Mehta J, Verber M, Wieser J, Schmit BD, Schindler-Ivens S. (2009). A novel technique for examining brain activity associated with pedaling using fMRI. Journal of Neuroscience Methods, 179 (2), 230-239.

Fields of Study

Major Field: Industrial and Systems Engineering

Table of Contents

Abstract ...... ii

Dedication ...... vi

Acknowledgments...... vii

Vita...... ix

List of Tables ...... xv

List of Figures ...... xvii

Chapter 1: Introduction ...... 1

1.1 Epidemiology of Low Back Pain ...... 1

1.2 Risk Factors to Low back pain ...... 2

1.3 Muscle Fatigue ...... 18

1.4 Muscle Fatigue and Adaptations ...... 25

1.5 Conceptual Model ...... 31

1.6 Specific Aims ...... 33

Chapter 2: Physiological and Biomechanical Responses to a Prolonged Repetitive

Asymmetric Lifting Activity...... 36

2.1 Introduction ...... 36

2.2 Methods ...... 41

2.3 Results ...... 48

2.4 Discussion ...... 59

2.5 Conclusions ...... 68

Chapter 3: Exploring Changes in Muscle Physiology and Lifting Behavior with

Combined Exposure to Whole Body Vibrations and Task Precision Demands ...... 69

3.1 Introduction ...... 69

3.2 Methods ...... 70

3.3 Results ...... 74

3.4 Discussion ...... 81

Chapter 4: Exploring the Effects of Seated Whole Body Vibration Exposure on

Repetitive Asymmetric Lifting Tasks ...... 84

4.1 Introduction ...... 84

4.2 Methods ...... 87

4.3 Results ...... 95

4.4 Discussion ...... 109

4.5 Conclusion...... 113

Chapter 5: Effects of Task Precision Demands on Behavioral and Physiological Changes during a Repetitive Asymmetric Lifting Activity ...... 114

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5.1 Introduction ...... 114

5.2 Methods ...... 117

5.3 Results ...... 124

5.4 Discussion ...... 134

5.5 Conclusions ...... 142

Chapter 6: Movement Variability during Repetitive Asymmetric Lifting Task...... 143

6.1 Introduction ...... 143

6.2 Methods ...... 145

6.3 Results ...... 146

6.4 Discussion ...... 154

6.5 Conclusion...... 158

Chapter 7: Overall Discussion ...... 159

7.1 Interpretation of the Results ...... 162

7.2 Limitations ...... 175

7.3 Future Directions ...... 177

7.4 Conclusion...... 179

References ...... 182

Appendix A: Results from no-vibration and repetitive lifting under low precision demands condition...... 202

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Appendix B: Results from correlation between oxygenated hemoglobin levels and biomechanical measures...... 207

Appendix C: Settings used for whole body vibration exposure...... 209

Appendix D: Matlab code used to analyze biomechanical data...... 212

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List of Tables

Table 1: p-values for the rating of perceived exertion (RPE) during the driving and the repetitive lifting phases of the experiment (bold text indicates p<0.05)...... 74

Table 2: p-values for the right oxygenated hemoglobin levels during the driving and lifting task (bold text indicates p<0.05)...... 75

Table 3: p-values for the spine kinematic and moment measures during the lifting task

(bold text indicates p<0.05)...... 75

Table 4: p-values for the spine kinematic measures during the driving task for the

FEMAP (bold text indicates p<0.05)...... 78

Table 5: p-values for the spine kinematic measures during the lifting task for the FEMAP

(bold text indicates p<0.05)...... 79

Table 6: p-values using the SD approach for the Lifting Data (vibration effect)...... 147

Table 7: p-values for the 95th percentile values during the repetitive lifting task...... 148

Table 8: p-values using the SD approach for the FEMAP...... 149

Table 9: p-values for the 95th percentile values during the FEMAP...... 151

Table 10: p-values using the SD approach for the Lifting Data (precision demands effect).

...... 152

Table 11: p-values for the 95th percentile values during the repetitive lifting task...... 153

Table 12: p-values using the SD approach for the FEMAP...... 153

Table 13: p-values for the 95th percentile values during the FEMAP...... 154

Table 14: p-values for the Borg rating and Tissue oxygenation measure during the seating and lifting task (VL condition)...... 203

Table 15: p-values for the mean and standard deviation data for the spine kinematic, moment and lift duration measures during the repetitive lifting task (VL condition). ... 203

Table 16: p-values for the spine kinematic measures obtained in between the seating and the lifting task during the FEMAP (VL condition)...... 205

Table 17: Correlation Coefficients between right oxygenated hemoglobin levels and spine kinematic and moment measures (bold indicate p < 0.05)...... 208

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List of Figures

Figure 1: Interactions of various risk factors to cumulative trauma and low back pain ..... 2

Figure 2: Factors affecting LBD risk (adapted from Marras 2008) ...... 5

Figure 3: Components of spinal stability (Panjabi 1992) ...... 13

Figure 4: Transmission of the IR light to the muscle cite (adapted from Ferrari et al.,

2004) ...... 22

Figure 5: Conceptual model for muscle fatigue and injury ...... 32

Figure 6: Schematic representation of the experimental layout...... 43

Figure 7: Regression lines for changes in the ratings of perceived exertion over the course of the lifting task for individual participants. Gray markers indicate the average regression line. Shorter lines indicate participants did not complete the 60-minute task . 49

Figure 8: Regression lines normalized to baseline values for the change in right erector spinae oxygenated hemoglobin over the course of the lifting task. Gray markers indicate the average regression line fit to all data. Shorter lines indicate participants did not complete the 60 minutes task. Individual lines are denoted by corresponding r2 values.. 51

Figure 9: Regression lines normalized to the first 10 minutes of lifting for forward bending motion (a), twisting motion (b) and lateral bending motion (c) during the repetitive lifting tasks. Gray markers indicate the average regression line. Individual lines are denoted by corresponding r2 values...... 52

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Figure 10: Regression lines normalized to the first 10 minutes of lifting for extension velocity (a), twisting velocity (b) and lateral bending velocity (c) during the lifting tasks.

Gray markers indicate the average regression line. Individual lines are denoted by corresponding r2 values ...... 54

Figure 11: Regression lines normalized to the first 10 minutes of lifting for forward bending moment (a), twisting moment (b) and lateral bending moment (c) during the lifting tasks. Gray markers indicate the average regression line. Individual lines are denoted by corresponding r2 values...... 56

Figure 12: Regression lines normalized to baseline (base) for sagittal plane range of motion (a), forward bending velocity (b), extension velocity (c), twisting velocity (d) during the FEMAP. Gray markers indicate the average regression line...... 58

Figure 13: Vibration x Task Precision Demand interaction for lateral bending motions of the spine (“*” indicates p < 0.05)...... 77

Figure 14: Three-way interaction between Vibration, Task Precision Demands and Time for twisting velocity of the spine (“*” indicates p < 0.05) ...... 78

Figure 15: Vibration x Task Precision Demand interaction for forward bending motions of the spine ...... 80

Figure 16: Vibration x Time for twisting velocity of the spine during the FEMAP (“*” indicates p<0.05) ...... 81

Figure 17: Experimental setup during the simulated driving task (a) and the lifting task

(b) ...... 89

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Figure 18: Borg rating - Vibration x time interaction for the Borg rating measure during the simulated driving (a) and the lifting task (b). Vertical bars indicate standard error of the mean. p values indicate significance of the effect over time...... 96

Figure 19: NIRS - Vibration x time interaction for the oxygenated hemoglobin levels obtained from the NIRS system during the simulated driving (a) and the lifting task (b).

Vertical bars indicate standard error of the mean ...... 98

Figure 20: Lifting - Vibration x time interaction for spine flexion (a), twisting (b) and lateral bending motion (c). Vertical bars indicate standard error of the mean. p values indicate significance of the effect over time...... 100

Figure 21: Lifting - Vibration x time interaction for flexion moment (a), twisting moment (b) and lateral bending moment (c). Vertical bars indicate standard error of the mean. p values indicate significance of the effect over time...... 102

Figure 22: Lifting - Vibration x time interaction for extension (a), twisting (b) and lateral bending (c) velocities of the spine. Vertical bars indicate standard error of the mean. p values indicate significance of the effect over time...... 104

Figure 23: FEMAP - Vibration x time interaction for peak range of motion in sagittal plane (a), flexion velocity (b), extension velocity (c) and lateral bending velocity (d) of the spine during the simulated driving task. Vertical bars indicate standard error of the mean. p values indicate significance of the effect over time...... 106

Figure 24: FEMAP - Vibration x time interaction for peak range of motion in sagittal plane during the lifting task. Vertical bars indicate standard error of the mean ...... 107

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Figure 25: FEMAP - Vibration x time interaction for forward bend (a), extension (b) , twisting (c) and lateral bend (d) velocities of the spine during the lifting task. Vertical bars indicate standard error of the mean. “*” indicates statically significant differences. p values indicate significance of the effect over time...... 108

The width of the opening on the destination conveyor was adjusted to control the task precision demands (dotted gray – high precision, solid gray – low precision)...... 119

Figure 27: Overall percent change in the levels of oxygenated hemoglobin normalized to the initial 10 minutes for the repetitive lifting task. Conditions connected by horizontal lines were not statistically different. Error bars represent standard error of the mean. . 125

Figure 28: Changes in the amount of spine flexion (a), lateral bending moment (b) and the three dimensional movement velocities (c) during the repetitive lifting task.

Conditions connected by horizontal lines were not statistically different. Error bars represent standard error of the mean...... 127

Figure 29: Changes in the overall lift duration (a) and placement times (b) during the repetitive lifting task for the low and high placement precision conditions. Error bars represent standard error of the mean...... 129

Figure 30: The area under the curve during the last 10% of the lifting task (box placement) for twisting motions (a) and lateral bending moment of the spine (b). Error

xx bars represent standard error of the mean. The “*” indicates where there were statistically significant differences between low and high task precision demands...... 130

Figure 31: A top view for the left hand trajectory data from an individual subject for the last 30 lifts (a); the solid lines are from lifts during the high task precision demand condition, and the dotted lines are from the low task precision demand condition. The lower chart shows the averaged areas under the curve across subjects for the left hand trajectory data during the lifting task as a function of the task precision demands (b).

Error bars represent standard error of the mean...... 132

Figure 32: Changes in spine motions (a), sagittal plane movement velocities (b) and out of plane movement velocities (c) over time based on FEMAP. Error bars represent standard error of the mean. Conditions connected by horizontal lines were not statistically different...... 134

Figure 33: Changes in the SD values for extension velocity of the spine as function of vibration exposure during the repetitive asymmetric lifting activity...... 147

Figure 34: Changes in the SD for twisting velocity of the spine as function of vibration exposure during the FEMAP, “*” indicates p < 0.05...... 150

Figure 35: 95th percentile twisting velocity as a function of vibration exposure during the

FEMAP, “*” indicates p < 0.05...... 151

Figure 36: Conceptual model revisited. Italics indicate inferences from the literature. . 161

Figure 37: Changes in spine kinematics with repetitive lifting task under low demands after exposure to WBV (VL)...... 204

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Figure 38: Changes in the lateral bending moment of the spine (magnitude and standard deviation) with repetitive lifting activity under low demands after exposure to WBV

(VL)...... 204

Figure 39: Changes in the lift duration data (magnitude and standard deviation) with repetitive lifting activity under low demands after exposure to WBV (VL)...... 205

Figure 40: Changes in the spine kinematic data in between the seating task for the

FEMAP (VL)...... 206

Figure 41: Changes in the spine kinematic data in between the lifting task for the FEMAP

(VL)...... 206

Figure 42: Screen capture for the settings used in the vibration condition...... 210

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Chapter 1: Introduction

1.1 Epidemiology of Low Back Pain

The problem of back pain is prevalent in many countries across the world. Back pain is not only associated with substantial financial costs but also affects the quality of life. It is said that about 75 - 80% of the population would experience an episode of back pain sometime in their life (Andersson, 1998). Low back disorders (LBD) represent the most common and most expensive musculoskeletal disorder experienced in the workplace. Approximately 90 billion dollars is spent on the treatment of back pain annually (Luo et al., 2004; Dagenais et al., 2008). According to the 2012 Liberty Mutual

Workplace Safety Index, overexertion injuries were the most common type of workplace injuries in 2010, accounting for approximately 27% of all workers compensation claims.

In their report, excessive lifting, pushing, pulling, holding, carrying and throwing were associated with these overexertion type injuries. Bureau of Labor Statistics (BLS) data reported overexertion injuries during lifting or lowering to account for 22 percent of the total sprains, strains, and tears in 2011 (BLS, 2012). Further, musculoskeletal disorder cases accounted for 33 percent of the total injury and illness cases in the BLS data.

Specifically, industries such as healthcare, manufacturing and distribution have been identified by BLS to have high incidence of back injuries (BLS, 2012). Moreover, truck drivers and material movers are reported to have the highest days-away-from-work

(56,950 cases) among the total injuries and illnesses. Within truck driving and material moving occupations, musculoskeletal injury to the back accounted for 35 and 44 percent of the total cases respectively (BLS, 2012). Forty-one percent of those injured in material moving and 33 percent of those injured in truck driving occupations experienced overexertion type injuries. Additionally, in 2012, BLS also reported that employment in transportation and material moving occupations will increase by 20% from 2010 to 2020

(BLS, 2012). These epidemiologic data indicate that injuries due to overexertion, especially those to the back, continue to be an area of concern in material moving and truck driving occupations.

1.2 Risk Factors to Low back pain

The etiology of low back pain is complex and multi-factorial. As shown in Figure

1, individual (personal), psychosocial, work-organizational and physical factors can contribute to the development of low back pain (NRC, 2001).

Figure 1: Interactions of various risk factors to cumulative trauma and low back pain 2

Epidemiological studies have identified personal (individual) factors that can predispose an individual to low back pain. Specifically, factors such as age (Hurwitz and

Morgenstern, 1997; Kopec et al., 2004), smoking (Frymoyer et al., 1980; Shiri et al.,

2010a), obesity (Shiri et al., 2010b; Heuch et al., 2010), genetics (MacGregor et al., 2004;

Battie et al., 2007) and previous history of an injury (Punnett et al., 1991; Ferguson and

Marras, 1997) have been reported to have high prevalence of low back pain.

Psychosocial factors are subjective factors that can impose psychosocial stress on the worker, thereby increasing the risk of low back disorder (Marras et al., 2000).

Specifically, studies have identified job dissatisfaction, job content, inter-personal relationships, job control, demands stress to be associated with LBP (Bigos et al., 1991;

Bongers et al., 1993; Devereux et al., 1999; Hoogendorn et al., 2000; 2002). In their study, Marras and colleagues (2000) showed the effects of psychosocial stress on neuromuscular response of individuals with different personality traits. Their results indicate that psychosocial factors interact with the biomechanical response to increase spinal loading. Specifically, introverted individuals were reported to have greater trunk muscle co-contraction and larger spinal loading as compared to extroverted individuals when both groups were exposed to psychosocial stress.

Work organizational factors at the job objectify the nature of the work process that can influence psychosocial work environment (Carayon et al., 1999). Factors including limited rest breaks, limited task flexibility, limited or extensive peer contact and frequent overtime have been identified to be associated with work-related musculoskeletal disorders (Bergqvist et al., 1995). Additionally, work culture and work

3 policy have also been shown to influence the development of work-related musculoskeletal disorder (Warren et al., 2000).

Over the past three decades epidemiological studies have found association between LBP and physical workplace factors. These include handling heavy loads

(Manning et al., 1984; Pope et al., 2002), vibration (Palmer et al., 2003; Okunribido et al.,

2008), repetitive manual lifting (Frymoyer et al., 1983; Marras et al., 1993), duration of exposure (Spurgeon et al., 1997) and awkward posture (Li et al., 1999). Even though each of the physical factors has individually been associated with the development of

LBP, the risk of injury is increased when workers are exposed to combination of these physical work factors.

Figure 2 shows how individual, psychosocial, work organizational and physical factors interact at different physical work intensities to increase the LBD risk (Marras,

2008). Specifically, at low levels of work intensity, psychosocial and individual factors may have a greater role in explaining the LBD risk; whereas for high work intensity levels, a larger part of the risk can be explained by physical workplace factors. Physical workplace factors can be dictated by work organizational factors that determines the nature and extent of the job.

Figure 2: Factors affecting LBD risk (adapted from Marras 2008)

Occupational driving and manual handling jobs have been associated with low back pain (LBP) (Okunribido et al., 2008), suggesting that those who engage in both of these activities, for example, product or package delivery, may be at even greater risk due to their exposure to repetitive lifting tasks and whole body vibration, both recognized risk factors for LBP (Okunribido et al., 2008). Individually, the physical factors such as repetitive work, vibration exposure, task demands, awkward postures etc, seen in delivery jobs have been associated with muscle fatigue and low back disorder (LBD) risk. This dissertation seeks to understand the nature of back injury risk associated with these occupational factors when encountered in combination.

Lifting and low back pain

Manual lifting tasks have been identified as a primary risk factor for the development of LBP, particularly when they require a large percentage of an individual’s

5 strength to perform these tasks (Chaffin, 1987). Manual handling tasks that involve repetitive bending or twisting have also been associated with the development of LBP

(Marras et al., 1993) even when modest loads are lifted. Studies have shown that spinal loading varies as function of lifting weight (Davis and Marras, 2000; Lavender et al.,

2003; Plamondon et al., 2012), workplace layout (Marras et al., 1997; Lavender et al.,

1999, 2003; Davis and Marras, 2005), hand coupling (Marras and Davis, 1998), task demands (Davis and Marras, 2003), frequency of lifts (Marras et al., 2006) and task asymmetry (Marras and Davis, 1998).

Laboratory-based biomechanical studies have shown the intensity of back muscle activation during a symmetric lifting task is proportional to the load weight handled

(Dolan and Adams, 1993), the reach distance (Kumar, 1997) and the height from which the lifts are initiated (Nielsen et al., 1998). Symmetric lifting tasks create a bending moment on the spine, thereby increasing the spinal compressive loads (Dolan and Adams,

1993). Based on the load-tolerance relationship, if the internal tissue loads exceed tissue tolerance limits, injury can occur (McGill, 1996).

The Lumbar Motion Monitor (LMM) model developed at the Biodynamics

Laboratory at The Ohio State University utilizes three-dimensional spine kinematics, three-dimensional kinetics and individual’s height, weight, trunk depth, trunk breadth along with muscle activation levels from the 10 trunk muscles to predict spinal loading during lifting activities (Marras et al., 1993). The model has demonstrated that for a large scale industrial and manufacturing jobs five factors including the amount of spine flexion, the twisting velocity, the lateral bending velocity, or the load moment

6 characterizes occupational jobs from low versus high risk specific to the low back region.

All these quantities could change with asymmetric lifting activity.

Manual lifting tasks performed in occupations are largely asymmetric (Marras et al., 1993; Lavender et al., 2012). Asymmetric lifting tasks involve twisting and lateral bending motions of the spine. Asymmetric motions are documented to increase co- contraction from the abdominal muscles (Lavender et al., 1992; Sommerich and Marras,

1992). Increased co-activation of the trunk musculature with asymmetric lifting has been reported to increase lateral and anterior-posterior (A-P) shear forces on the spine, in addition to compressive forces (Granata and Marras, 1995). Unlike compressive spinal loads, the human spine has low tolerance to shear forces (McGill, 1996). In addition, as loads are handled asymmetrically, the demands on agonist muscles increase as fewer muscles are available to share the load (Lavender et al., 1992) therein increasing the rate at which specific muscles fatigue and decreasing the margin of safety between the task demands and the maximal capability of the muscle tissue. Thus, the risk of injury associated with asymmetric lifting tasks is greater than symmetric lifting tasks.

Besides three-dimensional spine motions, there is also biomechanical evidence that suggests larger movement velocities impose greater spinal loads. Faster movement velocities have been reported to increase the net moment acting on the spine at L5/S1

(Dolan et al., 2001). During isokinetic lifting exertions, Granata and Marras (1995) showed faster lifting velocities resulted in larger compressive and shear loads on the spine. For a symmetric lifting task, faster movements have resulted in larger bending moment (Lavender et al., 2003) and greater compressive loads (Marras and Sommerich,

1991). While larger extension velocity during symmetric lifting activity can increase the compressive loads acting on the spine, larger twisting and lateral bending velocities seen during asymmetric lifting tasks increase the shear loading (Marras and Granata, 1997).

Larger movement velocities of the spine are also associated with greater co-activation of the trunk musculature (Dolan and Adams, 1993; Marras and Mirka, 1993). In sum, larger movement velocities during a lifting task will increase spinal loading.

Repetitive Lifting

While an injury can occur when biomechanical loading exceeds tissue tolerance limits (McGill, 1996), an injury can also occur even if the tissue loads are well under the tolerance limits as seen during repetitive lifting tasks (McGill, 1996; Punnet et al., 1991).

Here, continual wear and tear of the tissues over time can reduce the stress bearing capacity of the underlying structures (Kumar, 1990). Thus, the injuries due to repetitive manual work, specifically, repetitive lifting could be related to the development of muscle fatigue. Repetitive lifting tasks have been associated with the development of

LBP and muscle fatigue (Dempsey, 1998). Even though the biomechanical mechanism linking physical fatigue and LBP is not well established, one can understand this link by examining the effect of physical fatigue on the spinal system.

Muscles within the torso provide active support to the spine. Major bilateral muscle pairs of the torso that support and load the spine include multifidus, erector spinae, internal oblique, external oblique and the rectus abdominus. Deeper muscles include the psoas and quadratus lumborum muscles. These bilateral muscle pairs

8 provide the necessary force and stiffness when performing the spine motions (flexion, extension, twisting and lateral bending) or when stabilizing the torso in response to an external loading event. During a lifting activity, the brain recruits these muscle pairs to perform the motions and to counterbalance the external loads acting on the spine. As the muscles of the spinal system are in physical proximity to the spine, they are at a mechanical disadvantage when counteracting the external forces; therefore activation of these muscles imposes large loads on the spine. During a controlled spine movement task, muscles pairs may be recruited simultaneously to provide joint stability. In addition, the simultaneous activation of the torso flexors and the extensor muscles (co- contraction) can impose even larger loads on the spine.

Muscle fatigue due to repetitive lifting decreases the force generating capacity of the primary muscles (Sparto et al., 1997a). During a fatiguing flexion-extension movement task this has been reported as a significant decrease in peak and average torque generation capacity in the sagittal plane (Parnianpour et al., 1988). In order to compensate for the decrease in the force generating capacity of the primary muscles, antagonist muscles along with alternate agonist muscles may be recruited in generating the necessary force and maintaining controlled torso movements. For a controlled repetitive trunk extension task, Sparto and Parnianpour (1998) reported an increase in latissiumus dorsi and external oblique muscle activation with development of erector spinae fatigue. A similar increase in trunk muscle co-activity has been reported with the development of fatigue in the erector spinae muscles (Sparto et al., 1997a; O’Brien and

Potvin 1997). Even though co-activity increases the force output of the torso, increased

9 co-contraction has also been shown to increase spinal loading. Specifically, larger co- contraction has been shown to increase shear loading of the spine (Granata and Marras,

1995).

Ligaments are passive connective tissues holding the spine together.

Functionally, they limit motion, and generate force under tension (in non-neutral postures), therein providing support under these conditions. There is evidence that suggest muscle fatigue due to repetitive stooped lifting changes the viscoelastic properties of these passive structures (van Dieen et al., 1994). Specifically, this has been reported as increase in the creep behavior following back muscle fatigue (Shin et al.,

2009; Sanchez-Zuriaga et al., 2010). Creep (deformation) in the passive structures such as the ligament would reduce passive stiffness (resistance) to stretch, especially at the end range of motion. Behaviorally, this has been reported as increase in the range of motion in the sagittal plane (Dolan and Adams, 1998). The increased laxity of the spine due to a decrease in passive stiffness can lead to ligamentous damage and increase the stress on the inter-vertebral disc as the range of motion increases. Further, increase in laxity of the passive structures can also alter the neuromuscular response; this has been demonstrated in cats where viscoelastic creep due to cyclic loading reduced the muscular activity

(Solomonow et al., 1999)

The reflex response of the neuromuscular system relays accurate information to the muscles in order to generate the required force. Epidemiological study by Cholewicki et al. (2005) showed delay in the reﬂex response to signiﬁcantly increase the odds of sustaining a back injury. Previously, Moorhouse and Granata (2007) have reported reflex

10 response to account for 42% of trunk stiffness. Thus, a decrease in the reflex response would reduce the overall trunk stiffness and may increase spinal instability. Creep behavior following repetitive stooped lifting tasks or prolonged flexion has been reported to decrease the reflex response of the neuromuscular system (Granata et al., 2005; Rogers and Granata 2006; Sanchez-Zuriaga et al., 2010). Therefore, feedback control of the neuromuscular system can be disrupted following repetitive lifting activity with a stooped posture.

The effect of back muscle fatigue on the reflex response is inconclusive. By quantifying reaction times, Wilder et al., (1996) reported an increase delay in the reflex response following back muscle fatigue. In his kinematic test, Kelaher (2006) showed increase in muscle onset times for the extensor muscles with the development of muscle fatigue. Contrastingly, others have reported that muscle fatigue does not influence the reflex response of the neuromuscular system (Granata et al., 2004; Herrmann et al., 2006;

Dupeyron et al., 2010).

A delay in the feedback response of the neuromuscular system can lead to proprioceptive loss (Radebold et al., 2001). There is evidence that lifting induced fatigue can decrease spinal proprioception (Sparto et al., 1997a) and motor performance

(Gandevia, 2001). Following fatiguing exercises, studies have reported an increase in postural sway with whole body fatigue (Seliga et al., 1991; Nardone et al., 1997).

Increased postural sway can have adverse effect on postural stability. During fatiguing isokinetic trunk extension exertions, Kelaher (2006) reported an increase in trunk repositioning error and force replication error. Similarly, during a passive trunk rotation

11 task following back muscle fatigue, healthy subjects and patients with low back pain showed greater impairment to sense change in their lumbar spine movements (Taimela et al., 1999). This impaired ability of the spine to sense changes in position with the development of fatigue can increase spine and postural instability, thereby increasing the risk of injury especially during repetitive manual lifting tasks and tasks involving sudden loads.

Stability describes the ability to maintain spinal equilibrium despite the manifest presence of kinematic disturbances and motor-control errors (Moorhouse and Granata,

2007). For the spinal system to be stable, its subcomponents, active, passive and feedback control, should work in harmony to maintain equilibrium (Figure 3, Panjabi,

1992). If the stability criteria are not met, excessive forces can act on the tissue, thereby leading to spinal buckling and injury. There is evidence to believe that muscle fatigue due to repetitive lifting can lead to disruption of the active, passive and neural component of spinal stability. Specifically, the loss in muscle stiffness due to muscle fatigue has also been shown to be a primary factor contributing to spinal instability (Granata et al., 2004).

Creep in the viscoelastic structures of the spine following muscle fatigue due to repetitive lifting can reduce the passive stiffness, as well as increase delay in the neuromuscular response that can contribute towards passive and neural components of spinal stability

(Granata et al., 2005; Rogers and Granata, 2006; Sanchez-Zuriaga et al., 2010).

Figure 3: Components of spinal stability (Panjabi 1992)

In summary, epidemiological studies have linked repetitive lifting with the onset of low back disorders. Biomechanical studies have shown that repetitive lifting tasks can lead to the development of muscle fatigue. Muscle fatigue brings about neuromuscular changes of the spinal system that can affect the active, passive and neural components of spinal stability. Muscle fatigue due to repetitive lifting task can increase co-activation of the trunk musculature, lead to creep in the passive ligaments, and increase delay in the neural response, all of which can contribute through various mechanisms to an increased risk of back injury.

Lifting Task Demands

Manual lifting tasks are often performed in a restricted work space environment that requires varying degrees of precision as products are stacked on handtrucks, carts, and shelves. Higher precision demands are expected to affect the degree of muscle

13 control required while performing these tasks. In theory, higher precision of movement while working in restricted space can increase muscle activity due to static exertions

(Drury, 1985). The slower corrective movements during high precision tasks can be attributed to the speed-accuracy tradeoff (Fitts, 1954). Larger movement times with higher precision demands during the lifting task have been reported (Beach et al., 2006;

Stambolian et al., 2011). Thus, the slower sustained movements during precise work can increase muscle co-contraction in order to achieve joint stability, this can impose additional load on the joints within the body, and hasten the development of muscle fatigue. In their study, Davis et al., (2002) reported larger changes in trunk muscle activation levels along with changes in spine kinematic and kinetic measures when participants were asked to precisely place the box within a target area. These changes in muscle activity and spine biomechanics measures resulted in larger compressive and shear forces on the spine. A similar increase in spinal loads has been reported with high precision placement tasks (Davis and Marras, 2003). More recently, Beach and colleagues (2006) showed a similar effect of task precision demands on spinal loads during a symmetric repetitive lifting task. However, the effects of task precision demands during repetitive asymmetric activity on spinal loading have not been investigated.

Sustained muscle contraction during precise work has been demonstrated to increase the development of muscle fatigue (Jensen et al., 1993). Therefore, there is reason to believe that increasing the task precision demands also increases the rate of

14 fatigue development, especially during the static component of the task that requires sustained contractions.

Whole body vibration and Low back pain

Vibrations are mechanical energy oscillations that are transmitted to the body through a medium. Vibrations transmitted through the body are attenuated by the tissues in the body. If the frequency of oscillations matches the natural frequency of the tissues, resonance occurs. The resonance of the human spine has been reported to be between

4.5-8 Hz (Wilder et al., 1996; Panjabi et al., 1986). There is evidence to suggest that occupational WBV exposure at resonant frequency of the spine can contribute to an increased risk of low back disorders, sciatic pain, and degenerative changes in the spinal system (Bovenzi et al., 1999).

Epidemiological studies have identified a strong association between occupational driving and risk of LBP. Specifically, pilots, truck drivers, tractor drivers, bus drivers, taxi drivers, earth equipment movers have higher risk of LBP (Miyamoto et al., 2000;

Cann et al., 2004; Chen et al., 2005; Robb et al., 2007; Okunribido et al., 2008). Further,

Bovenzi (2010) found daily exposure to vibration to be a good predictor of LBP when they followed a healthy cohort for 2 year period. In addition to back pain, Magnusson and colleagues (1996) has also reported increase in neck and shoulder pain among occupational drivers.

Animal studies have provided direct relationship between disc degeneration and vibration exposure (Ekstrom et al., 1996; Yamazaki et al., 2002; Gregory et al., 2011).

Specifically, Ekstrom and colleagues (1996) reported disc deformation when porcine lumbar spines were exposure to 5Hz of sinusoidal vibrations for one hour. Additionally, disc herniation of the porcine cervical spine has been reported when specimens were exposed to 5 Hz vibrations (Gregory et al., 2011). In rabbits, Yamazaki et al., (2002) found vibration exposure to suppress aggrecan and collagen gene expressions after exposure to 6 Hz. Aggrecan and collagen gene expressions are essential in the spine’s response to compressive loads.

In humans, exposure to WBV has been reported to affect the intervertebral discs in the spine. Specifically, changes in the spinal height have been reported after exposure to whole body vibrations. (Sullivan and McGill, 1990; Magnusson et al., 1992; Pope et al., 1998). Magnusson and colleagues (1992), using a stadiometer, measured creep in the intervertebral discs and reported significant differences in height loss between the control group and the test group when exposed to 5 Hz whole body vibration for 5 minutes. In their model of the human spine, Keller and Nathan (1999) reported a majority of the height loss to be a direct result of disc deformation. Since the intervertebral discs act as shock absorbers and spacers between the vertebrae, any loss in fluid due to creep would reduce protection against the large compressive forces, change the vertebral mechanics, and change potential contact points between bones and nerve tissues.

The effect of WBV on development of localized muscle fatigue is not completely known. While Hansson and colleagues (1991) showed development of erector spinae muscle fatigue after exposure to WBV for five minutes, ElFalou et al., (2003) and de

Oliveira et al., (2004) reported no effect of WBV on the development of back muscle

16 fatigue. The differences in the seated posture could have led to differences in the fatigue measures. While, ElFalau et al. (2003) used a 25 degree reclined posture during their seated task, and participants maintained an upright seated posture in the study by de

Oliveria et al., (2004), Hansson et al., (1991) had participants seated in a flexed posture while holding a 4 kg load; this could have further activated the back muscles during the seated vibratory task. Further, Santos et al., (2008) reported development of muscle fatigue after exposure to WBV measured via changes in the frequency spectrum of the

EMG signal; however, the decrease in frequency content of the EMG signals were similar between quiet sitting and WBV exposure suggesting that the development of muscle fatigue was largely due to the seated task.

Neuromuscular reflex response of the spine can also be affected by exposure to

WBV. A study by Wilder and colleagues (1996) demonstrated an increase in latency and amplitude of the EMG signal to sudden loads after exposure to 5 Hz WBV. In another study, Li et al. (2008) reported an increase in reflex delay from 205 to 228 msec during sudden loading after exposure to 5Hz vibrations for 20 minutes. During a seated task, Arora and Grenier (2013) also reported an increase in the latency of the trunk muscles (at L3 and T9 levels) when exposed to 3 Hz WBV. It is interesting to note that the authors also found a similar change in the reflex response with quiet sitting. An increase delay in the feedback control can lead to an inhibition of muscle reflexes which normally protects the body against sudden loading by preventing joints from twisting or ligaments from rupturing (Carlsoo, 1982). Thus, the disruption in the feedback control of the spine can increase the risk of back injury especially under sudden loading.

1.3 Muscle Fatigue

In work physiology, muscle fatigue is defined as the decrease in the force generating capacity of the muscles. Localized muscle fatigue due to sustained contractions or repetitive manual work is of importance to physical ergonomists.

Sustained contractions during a static (isometric) task and repetitive or cyclic movements result in localized muscle fatigue of the peripheral muscles. In both cases, multiple factors including fiber type composition, intensity and duration of the contraction can affect the rate of fatigue development.

Skeletal muscles consist of two types of fiber composition; slow-twitch and fast- twitch fibers. Slow-twitch fibers (type I) are small sized fibers that use an aerobic metabolism to generate energy. These fibers functions to provide postural control and perform fine motor movements. These fibers can work for long periods of time and are resistant to fatigue. On the other hand, fast-twitch fibers (type IIa and IIb) are power generating muscle fibers, and are involved in gross motor movements. Specifically, type

IIa fibers are medium sized and rely on aerobic as well as anaerobic metabolism to generate energy. Whereas, type IIb fibers solely rely on anaerobic metabolism. Type II fibers are able to work from a few minutes to about 30 minutes and fatigue at a faster rate. Although both slow and fast twitch fibers generate similar amount of peak force

(Fitts and Widrick, 1996), the fast twitch fibers can generate the force at a greater speed as compared to slow twitch fibers.

Electromyography (EMG) and muscle fatigue

Electromyography is a technique used to measure electrical activity in the skeletal muscles. Every time a muscle undergoes a contraction, it creates an action potential; this electrical activity can be detected by an EMG measurement system. EMG samples can be obtained using surface electrodes on the skin or via intramuscular electrodes (wire and needle). While intramuscular sensors provide accurate information about the muscle activity from an individual motor unit, surface EMG has been widely used in the past to assess changes in the overall muscle activity. A typical surface EMG signal is comprised of electrical activity detected from the skeletal muscle fibers underlying the sensor site. The amplitude of this response provides information about the force generated by the muscle, whereas the frequency content provides information about the fiber type composition that contributes to the muscle activity. However, the use of surface EMG does not allow for measuring the activation of deeper muscles.

A well known technique to assess localized muscle fatigue from skeletal muscle is to quantify the spectral components of the EMG signal. Specifically, changes in the median and mean frequency response of the EMG signals have been used to measure localized muscle fatigue (Naeije and Zorn 1982; De Luca, 1997). The shift in the median and mean frequency response indicates changes in the muscle fiber composition contributing to the EMG signal. At the beginning of a lifting task, fast twitch fibers provide the necessary force in maintaining the overall force output; however, these fibers are also fast-fatiguing as they rely on anaerobic metabolism for adenosine tri-phosphate

(ATP) replenishment. Thus, at the beginning of a task, the EMG signal is comprised of

19 frequencies that are towards the higher end of the frequency spectrum. As the lifting activity is repeated or sustained, slow twitch fibers (that fire at slow frequencies) contribute more to the EMG signal. Thus, towards the end of the repetitive lifting task, the frequency spectrum is shifted towards lower frequencies as the majority of the EMG signal is contributed by the slow-twitch fibers.

Changes in the median and mean frequency response of the EMG signal are well studied during isometric tasks (Petrofsky and Lind, 1980; Dolan et al., 1995). Similar shifts in the median and mean frequency response have also been reported for dynamic lifting tasks (Potvin and Norman, 1993; Dolan and Adams, 1998, Bonato et al., 2003).

However, the majority of the studies that have assessed localized muscle fatigue during a dynamic repetitive lifting task have looked at the changes in the frequency content during an isometric activity at the beginning and towards the end of a lifting task, for example, tests are performed pre and post activity or in between bouts of the dynamic lifting tasks

(Potvin and Norman, 1993; Dolan and Adams, 1998; Bonato et al., 2003). This is one of the major limitations of measuring localized muscle fatigue during a dynamic task as the assessment requires disruption of the dynamic activity in order to perform the static isometric tests. Continuous monitoring of the frequency content of the EMG signal does not provide accurate assessment of localized muscle fatigue, during a dynamic task, because there are changes in the amount of force exerted, muscle length, rate of change in the muscle fiber length, as well as a temporary shift between the active muscle fibers and the location of the surface electrodes (Bonato et al., 2001). These changes would alter

20 the spectral components of the EMG signal during a dynamic task, thereby reducing the accuracy in detecting localized muscle fatigue.

Near-Infrared Spectroscopy (NIRS)

NIRS is a non-invasive optical imaging technique that directly and continuously measures changes in tissue oxygenation. The underlying principle of NIRS is the differential absorption of the Infra-Red (IR) light by muscle tissue. The NIRS system is comprised of a light source and detectors. The light source emits two wavelengths of near-infrared light (e.g. 760nm and 850nm) which is passed through the skin, bones and soft tissues beneath the sensors. This light is absorbed by the hemoglobin (Hb) and myoglobin (Mb) molecules in the blood stream. Due to similar absorbance spectra of the

Hb and Mb molecules it is difficult to differentiate Hb from Mb in an NIRS signal

(Mancini et al., 1994). Additionally, Mb only absorbs 10% of the IR light (Mancini et al., 1994). As for the two emitted wavelengths, the shorter wavelength is absorbed by the deoxygenated hemoglobin whereas the larger wavelength gets absorbed by oxygenated hemoglobin (Rolfe, 2000). The light reflected back to the detectors indicates the amount of oxygenated and deoxygenated hemoglobin levels in the blood (Figure 4).

Thus, NIRS provides a measure of oxygen delivery (oxygenated hemoglobin), utilization

(deoxygenated hemoglobin) and total blood volume (total hemoglobin = oxygenated + deoxygenated) at the tissue site.

Figure 4: Transmission of the IR light to the muscle cite (adapted from Ferrari et al., 2004)

Traditionally, NIRS has been used in neuroscience to understand changes in the level of oxygenation in the brain tissues (Villringer et al., 1993). When a certain part of the brain activates, there is increase in blood supply to the brain area, NIRS picks up the amount of tissue oxygenation in those areas as larger blood supply would imply larger oxygenated hemoglobin. Over the last decade, NIRS has also been used to understand changes in muscle physiology (McGill, Hughson and Parks 2000; Hamaoka et al., 2007).

While EMG provides information on the electrophysiological aspect of the muscles, NIRS provide a direct measurement of the physiological state by measuring the amount of oxygenation in the blood supply. Additionally, studies have shown the application of NIRS in assessing changes in muscle physiology during repetitive manual tasks (Yang et al., 2007; Ferguson et al., 2013). Further, there have also been several

22 studies in the literature that have demonstrated a direct link between tissue oxygenation levels (as determined by Near infrared spectroscopy) and localized muscle fatigue

(Yamada et al., 2008; Yoshitake et al., 2001; Ferguson et al., 2013). In their study,

Moritani et al. (1992) showed that ischemia due to occlusion of blood flow results in development of lactic acid along with decrements in median frequency response of the

EMG signal, indicators of muscle fatigue. Metabolite removal due to ischemia can be measured non-invasively via oxygenation levels detected from the NIRS signals. During

6-min cycling exercises at five different intensities, Miura and colleagues (2000) found very high correlations between oxygenated hemoglobin levels obtained from the NIRS system and the amplitude of integrated EMG response (an indicator of fatigue – Moritani et al., 1982) from the vastus lateralis muscle. Even during isometric arm movements,

Praagman and colleagues (2003) reported a linear relationship between a NIRS measure of deoxygenation and the amplitude of the EMG signals. Likewise, for isometric knee extension movements at 50% maximum voluntary contraction, Yamada and colleagues

(2008) showed a significant correlation of 0.8 between changes in tissue oxygenation levels and rate of change of the median frequency response obtained from the EMG signals. Similarly, for an isometric back extension exercise, Yoshitake and colleagues

23 shoulder movement task. In sum, these studies in the literature indicate that tissue oxygenation measures obtained from the NIRS signals can be useful to evaluate the physiological aspect of muscle fatigue.

Borg rating of perceived exertion

While EMG and NIRS signals provide objective measures of muscle fatigue, ratings of perceived exertion assesses the overall workload experienced by the person.

The Borg scale (Borg CR-10, Borg, 1982) has been used to evaluate subjective perception of fatigue (San Tho et al., 1997). One method of quantifying fatigue is by measuring the endurance time to failure. A study by Dedering et al., (1999) showed good correlations of Borg CR-10 with endurance time (r = 0.68) during their isometric task.

These authors also reported modest correlations between Borg ratings of perceived exertion and the slope of the median and mean frequency response of the EMG signals (r

= 0.41- 0.50). Moreover, at a Borg rating of 3, the median frequency, the mean frequency and the endurance time decreased by 30 percent. At a rating of 7, the median frequency, the mean frequency, and the endurance time decreased by 60-70 percent.

Similarly, during lifting tasks, studies have also shown an increase in the ratings of perceived exertion with development of localized muscle fatigue (Kimura et al., 2007;

Hummel et al., 2005; Looze, Bosch and Dieen 2009).

In addition to muscle fatigue, the Borg rating has also been associated with changes in the overall physiological workload (Borg et al., 1987). For an incremental hand cranking exercise, Capodaglio (2001) reported very high linear correlation (r =

0.99) between Borg CR-10 ratings and a combination of heart rate and blood lactate measures. Similar results have also been reported during bicycle ergometer work (Borg et al., 1985, Neely et al., 1992) and aerobic exercises (Coutts et al., 2009).

Even though there is evidence that suggests Borg CR-10 ratings to be a subjective assessment of muscle fatigue and overall physiological workload, one must be cautious while using this measure as a primary variable in assessing fatigue or physiological workload. Subjective perception of an individual during physical work can include factors such as pain, stress, discomfort, and other psychological variables.

1.4 Muscle Fatigue and Adaptations

The musculoskeletal system of the human body adapts with the development of localized muscle fatigue. Two theories have been proposed by the National Research

Council (NRC) related to these adaptations. One theory is that muscle fatigue brings about momentary muscle substitution patterns that result in more variable and less coordinated movements, while still maintaining the same overall behavioral strategy

(NRC, 2001). These variations in muscle use result in sporadic, but high, peak loads on the tissues which might lead to injury. Alternatively, in order to compensate for muscle fatigue, people may adapt their working strategy to prevent or accommodate fatigue development (NRC, 2001). This results in larger behavioral adaptations that can change an individual’s exposure to biomechanical risk factors. However, little is known about these adaptations in motor control and compensatory strategies and their potential effects on LBD risk.

Neuromuscular adaptations

Momentary muscle substitution patterns due to development of localized muscle fatigue result in more variable and less coordinated movements, while still maintaining the same overall behavioral strategy (NRC, 2001). For example, in order to compensate for the loss in strength due to back muscle fatigue, co-contraction of the antagonist muscles may occur in addition to agonist muscle activation to generate the required force and provide stability (Potvin and O’Brien, 1998), therein increasing loads on the secondary muscles. Secondary muscles are less suited for force generation, and due to their smaller size, may be more prone to overexertion injury. Muscle fatigue can also increase abdominal muscle activation. Specifically, during fatiguing isometric trunk extension exertions, Sparto et al., (1997b) reported an increase activation of the abdominal (internal oblique) and secondary extensor muscles (latissiumus dorsi) during an isometric endurance task. Both internal oblique and latissimus dorsi muscles impose shear loads on the spine (Granata and Marras, 1995). Similarly, Marras and Garanta

(1997) reported an increase in A-P shear force due to changes in the recruitment pattern of the trunk musculature during a 5-hour period of symmetric lifting activity.

In addition to increase in spinal loading, recruitment of secondary muscles can also lead to poorly coordinated movements. Experimentally, this has been reported as larger out-of-plane motions during a fatiguing isoinertial trunk flexion-extension task

(Parnianpour et al., 1988). In their 40-minute sagittally symmetric repetitive barbell lifting task, van Dieen et al. (1998) showed an increase in twisting motions of the spine with development of muscle fatigue. This increase in spine motions outside the plane of

26 movement during a fatiguing task could be attributed to delay in the neuromuscular response following muscle fatigue.

To prolong the development of muscle fatigue, the neuromuscular system may respond to increase the variability in the muscular and movement output. In their study, van Dieen et al. (1993) showed larger variability in the EMG signals for participants that showed larger endurance time (an indicator of fatigue); the authors suggested that the increased variability postponed the development of fatigue. Later, the authors showed limited variability in the EMG signals appears to expedite the fatigue process (van Dieen et al., 2009). Similar effects of motor variability on fatigue development have also been shown during fatiguing shoulder tasks (Falla and Farina, 2007; Farina et al., 2008). In addition to increased variability in the muscular response, studies have also reported an increase in cycle-to-cycle variability in the kinematic measures during repetitive fatiguing work. During a repetitive reaching task, Fuller and colleagues (2011) showed larger variability of the elbow and shoulder joints with the development of shoulder fatigue. A similar increase in movement variability has also been demonstrated by Gates and

Dingwell (2011) during their repetitive sawing activity. The larger movement variability during repetitive work may be a compensatory mechanism to generate the required force especially when primary muscles start to fatigue.

Behavioral adaptations

In compensating for muscle fatigue, people may also adapt their overall working strategy which can result in larger behavioral changes. Compensatory behaviors post

27 fatigue has been reported to provide stability and enhance motor performance (Bonato et al., 2003). Depending on the region of localized muscle fatigue, these adaptations have been seen as altering lifting style. For example, fatigue in the quadriceps muscles lead to alternation in the lifting style from a squat to a stoop lifting technique which was quantified via a decrease in knee moments and hip joint angles (Trafimow et al., 1993).

Additionally, following localized arm muscle fatigue, Chen (2000) reported participants performed stoop lifting in order to compensate for the lack of strength in the arm muscles. Similar shifts from squat to stoop lifting following back muscle fatigue have been reported in the literature (Sparto et al., 1997b; Bonato et al., 2003). Squat lifting has been reported to incur larger metabolic demands as compared to stoop lifts (Garg and

Herrin, 1979; Kumar, 1984). However, stoop lifting requires larger forward bending motions of the spine, which can increase the bending moment on the spine (Dolan et al.,

1994) and thereby increase the LBD risk. Thus, a behavioral change that leads to a stoop posture may be compensatory mechanism that reduces the overall energy expenditure during the repetitive lifting task at the cost of spinal loading.

Conversely, studies have also reported a change in lifting strategy from stoop to squat lifting technique (Bonato et al., 2003; Marras and Granata, 1997), suggesting redistribution of the load from the spine to the pelvis and lower extremities. Specifically, in their 5-hour manual depalletizing task, Marras and Granata (1997) reported alternation between spine and hip kinematics observed as a decrease in trunk flexion along with an increase in hip flexion over time. Here, changes in spine and hip kinematics resulted in

10% lower compressive force; however, the A-P shear forces increased by 35% indicating the increased risk associated with these adaptations.

During a fatiguing isokinetic trunk extension exertion task, Kelaher (2006) reported an increase in three-dimensional movement velocities of the spine following back muscle fatigue. However, the current literature on movement velocity adaptations during a repetitive lifting task is inconclusive. While, Trafimow et al. (1993) reported an increase in angular velocity during lifting with quadriceps fatigue, Sparto and colleagues

(1997b) found no change in movement velocities with their repetitive lifting task.

Further, Marras and Granata (1997) showed a decrease in sagittal plane spine movement velocity along with an increase in hip movement velocity in their 5-hour of manual depalletizing task. Although faster movement velocities may reduce the overall energy expenditure during the lifting task, it has been shown to increase co-activation of the trunk musculature (Dolan and Adams, 1993; Marras and Mirka, 1993) and spine loading

(Marras and Sommerich, 1991; Granata and Marras, 1995).

In addition to movement velocities, Chen (2000) reported larger forward bending acceleration levels of the spine in their repetitive lifting task following arm muscle fatigue. The increase in spine accelerations may be a mechanism to utilize the momentum of the box in facilitating the lifting task. For a repetitive lifting task, Bonato et al. (2002) showed larger box accelerations to increase the net torque acting at L4/L5.

Additionally, larger movement accelerations have been shown to increase abdominal muscle co-activation and spinal loading (Marras and Mirka, 1990).

Most of the research on behavioral adaptations during dynamic repetitive lifting mentioned above has focused on symmetric lifting tasks. As mentioned earlier, behavioral changes that increase the amount of forward bending, the twisting velocity, the lateral bending velocity, or the load moment, could alter LBD risk in repetitive lifting occupations (Marras et al., 1993). All of these quantities could change with prolonged asymmetric repetitive lifting. Only one study could be found that looked at behavioral adaptations during a repetitive asymmetric lifting task. In their 40 minutes of repetitive asymmetric lifting, Fraser and colleagues (2000) found a small decrease in spine flexion and reported no change in lateral bending and twisting motions of the spine. In their study, participants were free to choose their style of lifting and the spine kinematic measures were obtained during the lifting and lowering phases of the task. Thus, the decrease in the amount of spine flexion could be attributed to changes in the lifting behavior from a stoop to a squat posture. Since the spine kinematic measures were only compared from the initial five minutes of lifting/lowering task with the last five minutes of lifting/lowering task, it is difficult to conclude if there were any adaptations made during the entire course of the asymmetric lifting/lowering task while coping with the onset of muscle fatigue. Further, the data was collected simultaneously during lifting and lowering of the box, this would engage different muscles of the torso (Cresswell and

Thorstensson, 1994) and thus, the adaptations reported would be dependent on the type of task performed (lifting or lowering). In sum, little is known about the changes in lifting behavior that are suspected to occur with prolonged asymmetric repetitive lifting activity and their possible implications for back injury risk.

1.5 Conceptual Model

The conceptual model for this dissertation work is shown in Figure 5. This model hypothesizes that repetitive asymmetric repetitive stoop lifting task leads to the development of localized muscle fatigue in the erector spinae muscles. With the development of muscle fatigue, the musculoskeletal system adapts and brings about changes in the behavioral and neuromuscular responses that are hypothesized to decrease motor performance and increase the risk of back injury. Second, repetitive asymmetric lifting tasks that follow WBV exposure increase the rate of fatigue development in the erector spinae muscles as these muscles may be used in stabilizing the torso during the vibration exposure. Therefore, lifting preceded by WBV exposure is hypothesized to lead to larger decrements in motor performance and larger behavioral and biomechanical changes that further increases the risk of back injury as compared to the repetitive lifting task without prior exposure to WBV. Lastly, task precision demands imposed during repetitive lifting activity are also hypothesized to increase the rate of fatigue development and cause fatigue related changes in lifting behavior. The risk to back injury is hypothesized to be largest when high task precision demands during repetitive asymmetric lifting is preceded by exposure to WBV.

Figure 5: Conceptual model for muscle fatigue and injury

1.6 Specific Aims

Both manual material handling and trunk driving jobs have been individually identified with the development of muscle fatigue and low back pain. As mentioned above, muscle fatigue can bring about neuromuscular and behavioral changes that can affect the risk of back injury. The aim of this dissertation research is to understand the effects of combinational exposure to physical risk factors such as repetitive asymmetric lifting and vibration exposure on muscle fatigue development and altered lifting mechanics in ways that may predispose individuals to develop back injury. This dissertation work was conducted in the form of two separate studies.

Study 1 was exploratory and looked at the effect of repetitive asymmetric lifting activity on changes in muscle physiology, decrements in motor performance and changes in lifting behavior. Specifically, the aim of study 1 was to: investigate the effects of asymmetric repetitive lifting on measures associated with fatigue in the back muscles.

Hypothesis 1: Asymmetric repetitive lifting task leads to (a) decline in tissue

oxygenation levels, (b) behavioral adaptations that increase the peak values and

variability in kinematic and biomechanical measures, and (c) a deteriorated

ability to perform controlled spine motions.

Study 2 looked at the effects of repetitive asymmetric lifting and vibration exposure in combination on muscle physiology, motor performance deficits, and lifting mechanics. Specifically, the aims of this study were:

Aim 1: To investigate the effects of seated whole body vibration exposure on

measures associated with fatigue in the back muscles during a subsequent

repetitive lifting task.

Hypothesis 1: Relative to a repetitive lifting task that is not preceded by WBV

exposure, WBV exposure the precedes an asymmetric repetitive lifting task will

lead to (a) a larger decline in tissue oxygenation levels, (b) more pronounced

behavioral adaptations that increase the peak values and variability in kinematic

and biomechanical measures, and (c) a greater deterioration in the ability to

perform controlled spine motions.

Aim 2: To investigate the effects of repetitive lifting task’s precision demands

on back muscle fatigue measures.

Hypothesis 2: Lifting repetitively under high task precision requirements reduces

the variability in lifting behavior and therefore increases the rate of fatigue in the

back muscles measured through tissue oxygenation, behavioral adaptations, and

changes in motor performance measures relative to a lifting task with low

precision requirements.

Aim 3: To further our understanding of the interaction between vibration

exposure and task precision demands on measures of muscle fatigue during a

repetitive asymmetric lifting task.

Hypothesis 3: The combination of a lifting task with high task precision demands

that is preceded by WBV results in quicker fatigue development as measured

though tissue oxygenation, behavioral adaptations, and changes in motor

performance relative to experimental conditions with only whole body vibration

exposure or high task precision demands.

The organization of this dissertation

The dissertation work was conducted to test the aforementioned hypotheses.

Chapter 2 explored to understand behavioral and physiological changes associated with repetitive asymmetric lifting activity. Using the results obtained from Chapter 2, Chapter

3, 4 and 5 aimed to understand the effect of seated vibration exposure and lifting task precision demands on these behavioral and physiological changes. In addition to the overall changes, Chapter 6 looked at the variability in the behavioral response with the repetitive asymmetric lifting activity. The results obtained from study 1 (Chapter 2) and study 2 (Chapter 3, 4, 5 and 6) have been summarized in Chapter 7.

Chapter 2: Physiological and Biomechanical Responses to a Prolonged Repetitive

Asymmetric Lifting Activity

2.1 Introduction

Manual material handling tasks expose workers to stresses on their musculoskeletal and cardiovascular systems (Dempsey, 1998). Epidemiological studies in the past have shown an association between manual material handling tasks and low back pain (LBP) (Macfarlane et al., 1997; Hughes et al., 1997; Vandergrift et al., 2012;

Lavender et al., 2012). More specifically, manual handling tasks that involve repetitive bending, twisting, carrying or lifting movements have been associated with LBP (Marras et al., 1993; Hoogendoorn et al., 2002; Lotters et al., 2003; Heneweer et al., 2011;

Mikkonen et al., 2012; Lavender et al., 2012). In addition, repetitive lifting during manual handling tasks has been associated with muscle fatigue (Dempsey 1998).

However, the biomechanical mechanism linking muscle fatigue and back injury development has not been fully investigated. One theory is that muscle fatigue brings about altered behavioral strategies that changes an individual’s exposure to biomechanical risk factors (National Academy Press, 2001). Another theory is that momentary muscle substitution patterns result in more variable and less coordinated movements, while still maintaining the same overall behavioral strategy (National

Academy Press, 2001). These variations in muscle use result in sporadic, but high, peak loads on the tissues which might lead to injury.

Sparto et al. (1997b) reported that muscle fatigue due to repetitive lifting decreases the force generating capacity of the primary muscles. In order to compensate for the loss in strength due to back muscle fatigue, co-contraction of the antagonist muscles may occur to provide spinal stability (Potvin and O'Brien, 1998). There is evidence that back muscle fatigue can affect neuromuscular control of the spine

(Parnianpour et al., 1988; Kroemer 1992; Mawston, McNair and Boocock 2007; Granata and Gottipati, 2008) and decrease spinal proprioception (Sparto et al., 1997a; Taimela et al., 1999). Experimentally, this is seen as an increase in trunk repositioning error

(Kelaher, 2006), decline in motor performance of the trunk musculature (Parnaianpour et al., 1988; Sparto et al., 1996) and postural instability, for example, loss in balance (Sparto et al., 1996; Sparto et al., 1997b; Lin et al., 2012). This decrease in neuromuscular control can impose greater demands on the spinal structures.

In compensating for muscle fatigue during a repetitive lifting task, people may also adapt their working strategy which results in larger behavioral changes. However, little is known about the types of behavioral changes adopted and their effects on low back disorder (LBD) risk. Compensatory behaviors with repetitive lifting induced fatigue have been reported to alter spinal stability and motor control (Bonato et al., 2003;

Gregory et al., 2008). Depending on the region of localized muscle fatigue, these adaptations have been seen as altering lifting style, for example switching between stooped and squat postures when lifting (Trafimow et al., 1993; van Dieen et al., 1998;

Chen, 2000; Bonato et al., 2003). In addition, the higher forward bending acceleration levels with fatigue as reported by Chen (2000) suggest an altered lifting strategy post fatigue.

Most of the current research on behavioral adaptations during repetitive lifting has been focused on symmetric lifting tasks. The Lumbar Motion Monitor (LMM) model developed by Marras et al., (1993) indicates that behavioral changes that increase the amount of forward bending, the twisting velocity, the lateral bending velocity, or the load moment, could alter LBD risk in repetitive lifting occupations. All of these quantities could change with prolonged asymmetric repetitive lifting. In their work looking at behavioral adaptations during a 40-minute repetitive asymmetric lifting task, Fraser and colleagues (2000) found a small decrease in spine flexion and no change in lateral bend and axial motions of the spine. Here, spine kinematic measures were obtained during lifting and lowering of the box, and participants were free to choose their style of lifting.

Thus, the decrease in the amount of spine flexion could be a result of changes in the lifting style from a stoop to a squat posture. Since the spine kinematic measures were only compared from the first five minutes of lifting/lowering task with the last five minutes of lifting/lowering task, it is difficult to conclude if there were any adaptations made during the entire course of the asymmetric lifting/lowering task. Simultaneous lifting and lowering of the box would also engage different muscles of the torso

(Cresswell and Thorstensson, 1994) and thus, the adaptations reported would be dependent on the type of task performed (lifting or lowering). In sum, little is known

38 about the changes in lifting behavior that are suspected to occur with prolonged asymmetric repetitive lifting activity and its possible implications for back injury risk.

It is widely accepted that shifts in the frequency spectrum of electromyographic

(EMG) signals towards a lower frequency correspond to localized muscle fatigue (de

Luca, 1984; Soderberg and Knutson 2000). Recently, near infrared spectroscopy (NIRS) has been used to quantify changes in muscle physiology (McGill, Hughson and Parks

2000; Hamaoka et al., 2007). Further, there have also been several studies in the literature that have demonstrated a direct link between tissue oxygenation levels (as determined by Near infrared spectroscopy) and localized muscle fatigue (Miura et al.,

2000; Yamada et al., 2008; Yoshitake et al., 2001; Ferguson et al., 2013). In their study,

Moritani et al. (1992) showed that ischemia due to occlusion of blood flow results in development of lactic acid along with decrements in median frequency response of the

EMG signal, indicators of muscle fatigue. Metabolite removal due to ischemia can be measured non-invasively via oxygenation levels detected from the NIRS signals. During

6-min cycling exercises at five different intensities, Miura and colleagues (2000) found very high correlations between oxygenated hemoglobin levels obtained from the NIRS system and amplitude of integrated EMG response (an indicator of fatigue – Moritani et al., 1982) from the vastus lateralis muscle. Even during isometric arm movements,

Praagman and colleagues (2003) reported a linear relationship between NIRS measure of deoxygenation and amplitude of the EMG signals. Likewise, for isometric knee extension movements at 50% maximum voluntary contraction, Yamada and colleagues

(2008) showed a significant correlation of 0.8 between changes in tissue oxygenation

39 levels and rate of change of the median frequency response obtained from the EMG signals. Similarly, for an isometric back extension exercise, Yoshitake and colleagues

(2001) showed a decrease in median frequency of EMG signals along with decrease in tissue oxygenation measures that reduced at the onset of exercise. More recently, by utilizing both NIRS and EMG, Ferguson and colleagues (2013) showed that there was a decrease in median frequency response of the anterior deltoid and trapezius muscle along with decrease in tissue oxygenation at those muscle sites during a repetitive low intensity shoulder movement task. In sum, these studies in the literature indicate that tissue oxygenation measures obtained from the NIRS signals can be useful to evaluate physiological aspect of muscle fatigue.

The aim of the current research is to understand the physiological and biomechanical changes associated with repetitive asymmetric lifting as often observed in occupational lifting tasks (Marras et al., 1993). Specifically, repetitive asymmetric lifting is hypothesized to: (1) decrease tissue oxygenation; (2) increase sagittal plane movement errors while performing controlled spine flexion-extension motions; (3) result in behavioral adaptations during a defined lifting task as evidenced by changes in spine kinematic measures; and (4) increase biomechanical loading of the spine.

2.2 Methods

Experimental Design

Independent Variables

A repeated measures design was used in which participants repetitively lifted a box over a 60-minute period using a stoop posture. The weight of the box was adjusted to

15% of the participant’s maximum lifting strength. Thus, time spend during lifting was the independent variable investigated in this study.

Dependent Variables

The Borg CR-10 scale was used to capture changes in the subjective workload over time. Changes in muscle physiology were assessed using blood volume (total hemoglobin), oxygenated hemoglobin and deoxygenated hemoglobin levels derived from the NIRS signals. Behavioral and biomechanical changes during the lifting task were assessed using measures of lift duration, three-dimensional spine kinematics between (T1 and S1) and three-dimensional spine moments computed using a linked-segment model.

In addition, sagittal plane position error and out-of-plane spine motions in the axial and coronal planes were evaluated during a flexion-extension motion assessment protocol

(FEMAP) to assess changes in trunk motion control during a prolonged repetitive asymmetric lifting task.

Subjects

17 healthy volunteers, 11 males and six females between the ages of 19 and 44

(mean = 21.7 years, s.d. = 5.9 years) participated in the study. Mean height and weight of the participants were 1.75 m (s.d. = 0.09 m) and 79.7 kg (s.d.=19.1 kg). Participants had no prior history of musculoskeletal disorders of the back, neck, shoulder, arms and legs within the past six months. All participants were recruited from university student population and had no experience in manual material handling jobs. All participants signed an institutional review board (IRB) approved consent document prior to participating.

Apparatus

A passive structure was constructed from CreformTM materials to create a circular conveyor system. Lifts originated from a height of 0.25 m above floor level and terminated 0.86 m above floor level. The origin and destination conveyors provided 90 degrees of asymmetry to the participants left side (see Figure 6). The conveyor frames were fitted on top of Inscale force scales to capture the lift initiation and termination times. The participants lifted a wooden box (0.4 x 0.3 x 0.25 m) with handles. The box was filled with reams of paper to adjust the weight.

Figure 6: Schematic representation of the experimental layout

Self report measures (Borg CR-10 scale, Borg, 1982) were obtained to quantify change in the overall subjective workload with repetitive asymmetric lifting.

Near-Infrared Spectroscopy (NIRS) was used to evaluate changes in muscle physiology. The NIRS system provides a direct measurement of oxygen delivered and utilized at the muscle site. A two-channel INVOS 4100 Cerebral Oximeter (Somanetics

Corporation, Troy, MI, USA) was attached to the erector spinae muscles at L3 level.

Changes in blood volume (total hemoglobin), oxygenated hemoglobin and deoxygenated hemoglobin levels were continuously monitored at 85 Hz.

Three-dimensional spine motions were captured (at 120 Hz) using a magnetic motion capture system (The Motion Monitor TM, Chicago, IL) to understand spine kinematic changes associated with the repetitive asymmetric lifting task and performance changes during the FEMAP. Bertec (Bertec Corp, Columbus) force plates were used to 43 measure ground reaction forces that provided input into a three-dimensional dynamic linked-segment model within the Motion Monitor System that is designed to predict the three-dimensional moments acting at L5/S1. Two Inscale (Terra Haute, Indiana) force scales were used to identify the timing of the initial lift and the box placement in the collected data stream during the lifting trials. Maximum lifting strength, used to scale the box weight to each individual participant’s capability, was measured using a dynamometer.

Procedure

After signing an informed consent document (approved by The Ohio State

University Institutional Review Board), participants were attached to 11 motion capture system sensors: on top of the head, at the top of the thoracic spine (T1), over the top of the sacrum (S1), and bilaterally on the upper and lower arms and legs using Velcro straps and tape. Additionally, two NIRS sensors were placed bilaterally on the erector spinae muscles at the L3 level.

Each participant’s lifting strength was assessed using an maximum isometric assessment in which the participant attempted to pull upwards on a handle located at the same height as the handles on the box during the lifting task. This task was repeated, separated by two minutes of rest, until two maximum values were obtained that were within 10 percent of each other (Kroemer and Marras 1981). The strength data were used to adjust the box weight to 15% of maximum lifting strength (indicated by the larger of

44 the two exertions measured with the force monitor). On average, the box weighed 9.55 kg (s.d. = 3.08 kg).

Participants performed five minutes of warm-up back stretching exercises. Blood volume (total hemoglobin), oxygenated hemoglobin and deoxygenated hemoglobin levels from NIRS system were obtained during this period. Prior to starting the lifting task, maximum range of motion (ROM) in the sagittal plane was evaluated. With eyes closed, participants were asked to bend forward maximally to obtain each individual’s maximum trunk flexion capacity.

The Lifting Task

The participants were asked to grasp the handles and repetitively lift a box from a conveyor in front of them (0.25m above the floor) and place it to the conveyor located to their left side (0.86m above floor) without moving their feet and incorporating a stoop posture. The task was paced so that the participants performed 10 lifts/minute for 10 minutes. An audio signal, provided every six seconds, indicated when the lifts were to be initiated. At the end of each 10-minute lifting period, the flexion-extension motion assessment protocol (FEMAP) was performed and a Borg scale rating was obtained, after which another 10-minute period of lifting was initiated. This process of lifting for 10 minutes, followed by FEMAP continued until 60 minutes of lifting was completed or until the participant indicated they were fatigued and were no longer able to continue. Where participants decided to stop before the completion of the 60-minute lifting period, a final

FEMAP was performed and a Borg rating was obtained.

Participants were given an opportunity to practice the lifting task before starting the first 10-minute block of lifts. During this time, participants selected a foot position that they were asked to use throughout the lifting session. Typically, this posture resulted in 10 degrees of lift asymmetry towards the participants’ right side during the initial lift.

Participants were also instructed not to move their feet during the lifting task. An experimenter informed the participants if they inadvertently changed their foot position.

Flexion-Extension Motion Assessment Protocol (FEMAP)

Given that Parnianpour and colleagues (1988) reported out-of-plane motions became more prevalent with localized back muscle fatigue, a procedure was developed to evaluate the trunk kinematic performance in between each 10-minute block of box lifting.

In this procedure the participants, with their eyes closed, repeatedly flexed forward to a target position that was defined as two-thirds of their maximum trunk flexion capacity as fast as they could and returned back to an upright standing posture. These motions were repeated 10 times during which spine kinematic data were collected. Spine position information was provided via auditory feedback in that an auditory tone occurred when participants reached the target position and when they returned back to their upright standing posture. This assessment protocol, which only interrupted the lifting for approximately 30 seconds, was similar to other studies in the literature that have assessed movement behavior of the trunk (Swinkels and Dolan, 2000; Kelaher, 2006). Prior to data collection during this protocol, participants were instructed to practice the flexion-

46 extension task till they felt comfortable with this procedure, specifically, moving with the auditory feedback.

Data Analysis

Self report scores obtained from Borg scale ratings were used to identify changes in subjective workload over the 60 minutes of repetitive lifting activity. For the muscle oxygenation measures, the average across each 10-minute block of the lifting activity was computed. These data were normalized in terms of percent change from baseline values.

Studies in the past have used percent change as a way of quantifying changes in NIRS measures across participants (Miura et al., 2000; Ferguson et al., 2013). For the FEMAP, sagittal plane position change was calculated by averaging the peak deviations in the sagittal plane movements relative to the movement targets. Out of plane movements were analyzed by extracting the peak deviations in lateral bending and twisting motions. To assess behavioral and biomechanical changes during the prolonged lifting task, the peak three dimensional spine kinematics and moments were obtained for each lift. The timing of the individual lifts was calculated based on the force scale data. Means across each 10-minute block of lifting data were computed for lift durations, peak kinematic and moment measures.

These changes in these mean values were used to indicate the behavioral and biomechanical adaptations that occurred during the repetitive lifting task.

For each of the measures described above, univariate linear regression equations were derived using the 10-minute block means for each individual participant. For the participants that were not able to complete the 60 minutes of the repetitive lifting task,

47 fewer points were used in the generation of these regression equations. Using IBM SPSS

(version 19), a one-sample t-test was conducted to identify whether the distribution of slopes of the regression equations across the subjects were significantly different from zero for each of the dependent measures (p < 0.05). Additionally, a correlation analysis was performed between the NIRS measures and the spine kinematic and kinetic measures that showed significant changes during repetitive lifting task in order to understand the association between changes in muscle physiology and spine biomechanics during the prolonged repetitive asymmetric lifting task.

2.3 Results

Subjective workload

Figure 7 shows the regression functions derived for each individual participant’s ratings of perceived exertion sampled at the completion of each 10-minute block of the repetitive asymmetric lifting task. Overall, the slopes of the regression equations were significantly greater than zero (p < 0.001) with an average increase in rating of 0.64 units for every 10 minutes of repetitive lifting activity. While most participants followed this general trend, Figure 7 shows that there were a small number of individuals who reported very little change in their perceived exertion ratings. In addition, it is interesting to note the variation in the initial values obtained after the first 10 minutes of lifting. Further, subjective workload ratings during the repetitive lifting task also showed significant correlations (r = -0.838) with the NIRS measure of oxygenated hemoglobin (p<0.05).

9 8 7 6 5 4 3 2 1 Rating of percieved exertion percieved of Rating 0 0 10 20 30 40 50 60 Time (minutes)

Changes in the Near-Infrared Spectroscopy Measure

The near-infrared spectroscopy data were used to quantify changes in the erector spinae muscle physiology. The three measures obtained from the NIRS system were highly correlated. Specifically, the correlations between oxygenated hemoglobin and total hemoglobin for the left and right erector spinae muscles were 0.99. High correlations between deoxygenated hemoglobin and total hemoglobin (0.97 and 0.98) were also found for the left and right side. Similar high correlations were also observed between deoxygenated hemoglobin and oxygenated hemoglobin for the left and the right erector spinae muscle (0.95 and 0.97 respectively). Additionally, for all three measures

49 obtained from the NIRS system, there was also high correlation between the left and the right erector spinae muscles. Further, a paired t-test comparison showed no significant difference between the left and the right side for all three measures (p > 0.05).

Considering the significant task asymmetry to the left side during load placement and high correlations between the NIRS measures, the next set of NIRS results focus on the changes in oxygenated hemoglobin obtained from the right erector spinae muscle.

Figure 8 shows the regression functions normalized to the baseline value for oxygenated hemoglobin levels derived for each individual participant. Overall, the slopes of the regression functions were significantly below zero (p < 0.001). On average, right erector spinae oxygenated hemoglobin dropped by about 40% towards the end of the repetitive asymmetric lifting task. The participants who were not able to complete the 60 minutes of repetitive lifting activity showed larger declines in their tissue oxygenation measure. Those showing only small declines in the oxygenated hemoglobin also showed low r-squared values (Figure 8).

1.2 1

0.8 0.6

Hemoglobin 0.4

0.2 Normalized Oxygenated Oxygenated Normalized 0 Baseline 10 20 30 40 50 60 Time (minutes)

Behavioral changes with repetitive asymmetric lifting

During the repetitive asymmetric lifting task, the lift durations decreased significantly over time with slopes of the regression function significantly lower than zero (p = 0.022). On average, lift duration decreased by 9% towards the end of the repetitive lifting task as compared to the initial 10 minutes of repetitive lifting.

Figure 9 shows the individual regression functions normalized to the initial 10 minutes of lifting task for the spine motion data. The amount of forward bending motion showed a significant linear increase over time (p = 0.002). Even though there is considerable variability across subjects, on average, the amount of forward flexion increased by an average of 2.1 degrees/ 10 minutes of repetitive lifting. No significant changes in the amount of spine twisting (Figure 9b) and lateral bending (Figure 9c) were found during the repetitive lifting task.

Individual regression functions for the three-dimensional spine movement velocities, normalized to the initial 10 minutes of lifting activity, are shown in Figure 10.

On average, slopes of the regression function for extension (p = 0.001) and lateral bending velocities (p = 0.014) were significantly greater than zero. Extension velocity increased by an average of 3 degrees/second, and lateral bending velocity increased by an average of 1.65 degrees/second for every 10 minutes of repetitive lifting activity.

However, the twisting velocity showed no change during the repetitive asymmetric lifting task (p = 0.359).

Figure 10: Regression lines normalized to the first 10 minutes of lifting for extension velocity (a), twisting velocity (b) and lateral bending velocity (c) during the lifting tasks. Gray markers indicate the average regression line. Individual lines are denoted by corresponding r2 values

Figure 11 shows the regression functions, normalized to the initial 10 minutes of repetitive lifting, for the three dimensional spine moments. Overall, only the lateral bending moment of the spine decreased significantly during the repetitive lifting task (p =

0.001) with an average decrease of 2.6 Nm for every 10 minutes of repetitive lifting activity. Forward bending (Figure 11a) and twisting moments on the spine (Figure 11b) did not show any significant trends during the repetitive lifting task.

Spine kinematic variables that showed significant changes during the repetitive lifting task also showed significant negative correlations with the NIRS measure of oxygenated hemoglobin (p<0.05). Specifically, across the 60 minutes of lifting activity there were significant correlations between the NIRS measure of oxygenated hemoglobin and the extension velocity (r = -0.55), the lateral bending velocity (r = -0.52), the amount of forward bending motion (-0.65) and the lateral bending moment of the spine (r = 0.53).

Flexion-extension Motion Assessment Protocol (FEMAP)

Individual regression functions were derived for the spine kinematic measures, normalized to the baseline data, collected during the FEMAPs conducted after each 10- minute block of lifting. Four kinematic measures show significant trends in which the slopes of the regression functions were significantly different than zero. Figure 12a shows normalized individual regression functions for the amount of forward flexion.

Overall, the forward flexion increased by an average of 2.8 degrees after every 10 minutes of repetitive lifting. No significant trends were observed for the maximum amount of twisting or lateral bending across the FEMAPs scheduled over the 60-minute lifting period.

As for the movement speeds, the forward bending velocity, the extension velocity and the twisting velocity significantly increased across the 7 FEMAP samples (p<0.005).

In addition, the lateral bending velocity showed a marginal increase (p = 0.068). On average, the flexion and extension velocities increased by 7.5 and 10.5 degrees per second, respectively, after every 10 minutes of lifting. The twisting velocity increased, on average, by 1.8 degrees/second for every 10 minutes of repetitive lifting.

2.4 Discussion

In this exploratory study, participants performed a repetitive asymmetric lifting task with a stooped posture at the rate of 10 lifts/minute for 60 minutes. Overall, the ratings of perceived exertion increased over time. Likewise, the oxygenated hemoglobin levels from the erector spinae muscles, the muscle physiology measure, decreased over time during the prolonged lifting task. Behavioral measures suggest that the participants tended to lift faster over time as evidenced by shorter lift durations and faster extension and lateral bending velocities. However, the lateral bending moments acting on the spine decreased over time with repetitive lifting.

Subjective workload

Borg scale ratings were used in this study to quantify subjective perception of the overall physiological workload. Over the course of the lifting task, the Borg ratings increased linearly over time. Thus, participants perceived the overall workload to increase with sustained repetitive asymmetric lifting. Previous studies in the literature that have used repetitive lifting task protocol have also seen similar increase in the level of perceived physical effort over time (Garg and Banaag, 1988; Bonato et al., 2003; Lotz,

Agnew, Godwin and Stevenson 2009). Additionally, the increase in subjective rating of perceived exertion reported here has been previously demonstrated to increase with development of muscle fatigue (Kimura et al., 2007; Hummel et al., 2005; Looze et al.,

2009).

In this study, three of the 17 participants reported small to no change in their ratings of perceived exertion over time (Figure 7) despite a linear decrease in their muscle physiology measures. This mismatch between the subjective assessment of the overall workload and muscle physiological response could put these individuals at a greater risk of injury when performing repetitive lifting activity.

Muscle physiology measures

Tissue oxygenation measures obtained from the NIRS system were used to quantify changes in erector spinae muscle physiology. In spite of the asymmetry in the lifting task, erector spinae muscle physiology measures were not statistically different between the right and the left side. In this study, the box was always picked up at near ankle height which poses greater physiological demand (Garg and Banaag, 1988) and higher activation of the erector spinae muscles as compared to when lifting from waist height (Granata and Wilson, 2001). Additionally, placing the box near waist level with asymmetry leads to larger involvement from the abdominal muscles (Kim and Chung,

1995; Granata and Wilson, 2001). Thus, the changes reported here are primarily based on the erector spinae muscle physiology during the lifting phase of the movement as opposed to the placing phase.

All three measures of muscle physiology obtained from the NIRS system were highly correlated. However, the magnitude of change in oxygenated hemoglobin (40%) was larger than the changes in total hemoglobin (30%) and deoxygenated hemoglobin

(20%), implying that oxygenated hemoglobin was more sensitive to changes in muscle

60 physiology during the prolonged repetitive asymmetric lifting task. Studies using an isometric back extension task (Yoshitake et al., 2001) and a repetitive shoulder motion task (Ferguson et al., 2013) have identified changes in oxygenated hemoglobin as providing the earliest measure of muscle fatigue. In theory, the decrease in hemoglobin levels reported in this study would imply occlusion of blood flow leading to metabolic removal which may lead to muscle fatigue (Moritani et al., 1992; Perry et al., 2010).

This is further supported by studies showing the development of muscle fatigue, as measured with EMG spectral analysis, is associated with decrease in oxygenated hemoglobin levels (Miura et al., 2000; Yamada et al., 2008; Yoshitake et al., 2001;

Ferguson et al., 2013). Thus, decrease in oxygenated hemoglobin levels reported in this study suggests the development of fatigue in the erector spinae muscles due to the repetitive lifting activity.

Behavioral adaptations

Behavioral adaptations during a symmetric repetitive lifting task have been documented in prior studies. Most notably this has been reported as alternation between stoop and squat lifting techniques (Trafimow et al., 1993; Bonato et al., 2003) and between trunk and hip kinematics (Sparto et al., 1997b; Marras and Granata, 1997). In this study, participants were restricted from using their lower extremity to perform the lifts. Hence, the results demonstrate behavioral and biomechanical changes that occur within the stoop technique during lifting.

Overall, our hypothesis that prolonged repetitive asymmetric lifting leads to behavioral changes was supported. Our findings are in agreement with other studies in the literature that have shown increase forward bending motions with repetitive lifting

(Sparto et al., 1996, 1997b; Dolan and Adams, 1998). Comparing maximum sagittal flexion data obtained during the baseline FEMAP with the lifting data, it is evident that as participants repetitively lifted the box in a stooped posture they bend more over time; thereby, reaching closer to their end range of motion in the sagittal plane. This increase in laxity of the spine can be attributed to creep in the passive structure of the spine

(Adams and Dolan, 1996, Parkinson et al., 2004). Lifting at the end of range of motion implies working towards the end of their length-strength curve which can reduce an individual’s capacity for performing the lifting task and also increase the risk of overloading the passive stabilizing structures. Thus, the increased forward flexion can increase the risk of low back pain.

The increase in forward bending motions was not accompanied by increase in forward bending moment (FBM) of the spine. For a symmetric repetitive lifting task, increase in peak bending moment is associated with increase in peak flexion (Dolan and

Adams, 1998). This discrepancy in moment results could be due to differences in calculation of the spinal moments. While Dolan and Adams (1998) used an EMG based estimation of internal spinal moments, the current study calculated the external moments based on a three-dimensional linked- segment model. The differences in the fidelity of these models could account for the differences in the findings. Looking closer at the forward bending moment data (Figure 11a), it can be seen that some participants showed

62 an increase in their forward bending moments over time while for some decreased their forward bending moments over time. Further, correlations between the forward bending moment and other behavioral measures collected during the lifting task revealed a significant correlation between the forward bending moment and the horizontal reach distance (r = 0.41, p <0.0001) suggesting the role of horizontal reach distance in modulating the forward bending moment during a prolonged repetitive lifting task

(Lavender et al., 1999).

Due to asymmetry in the lifting task, we expected to see changes in twisting and lateral bending motions of the spine with repetitive lifting. Overall, no changes in these motions were observed. These results are in agreement with Fraser and colleagues

(2000) that have found no change in lateral bending and axial motions of the spine during their 40 minutes of asymmetric repetitive lifting tasks. The destination conveyor in this study had guide rails mounted on them which required precision during box placement.

There was a 6 mm gap on both the left and right sides between the box and the guide rails. This constraint on the task, along with the restriction on foot movement, may have limited the degrees of freedom available for behavioral adaptation. This could explain the null effect observed for the twisting and lateral bending motions. Future studies can look into whether task precision demands affects the behavioral adaptations made during the repetitive asymmetric lifting task.

The lateral bending moments on the spine decreased significantly over time among 13 out of the 17 participants in this study. Lateral bending moments of the spine are associated with lateral shear loads (Marras et al., 1999); thus reducing these moments

63 would potentially reduce the lateral shear loads on the spine in these individuals. A closer look at the data showed that different strategies were used by the participants to reduce their lateral bending moments. Some of the participants (N = 10) showed a lateral shift of the sacrum towards the destination conveyor while placing the boxes which reduced the horizontal reach distance and thereby reduced the lateral bending moment (Lavender et al., 1999). Additionally, some of the participants (N = 9) showed larger twisting motions of the spine towards the end of the repetitive lifting task as compared to the initial 10 minutes of the repetitive lifting activity. The increase in spine twisting motion reduced the lateral bending of the torso and the lateral bending mo ment, but likely increases the co-contraction of the trunk musculature (Marras and Granata,

1995) and resulting spine loads.

Unlike lateral bending moments, twisting moments did not change with the repetitive lifting task. A significant correlation (r = 0.41) between twisting moment and pelvic bending while lifting the box suggest different strategies were used by participants.

In our study, participants were free to choose their feet position which typically yielded

10 degrees of asymmetry to the right while picking the boxes. This would have led to some participants altering their hip kinematics while picking the box thereby leading to individual variation in twisting moments (Figure 11b).

Given the fixed rate of repetitive lifting activity (10 lifts/minute), participants shifted towards a strategy that resulted in reducing lifting duration, thereby increasing their waiting time between lifts. Biomechanically, the decrease in lift duration corresponded to an increase in extension and lateral bending movement velocities of the

64 spine. Increased movement velocities are associated with increased risk of back injuries in repetitive material handling jobs (Marras et al., 1993). Current literature on movement velocity adaptations during a repetitive lifting task is inconclusive. While Trafimow et al. (1993) reported an increase in angular velocity during lifting with quadriceps fatigue,

Sparto and colleagues (1997b) found no change in movement velocities with their repetitive lifting task. Previously, Granata and England (2006) have reported augmentation of spinal stability with faster movements; however, there have been no studies that have measured spine stability at different movement speeds during a repetitive asymmetric lifting task. For an isokinetic knee flexion-extension task

Granacher et al. (2010) suggested that an increase in angular velocity at the knee joint can provide necessary stiffness to improve gait stability with the development of muscle fatigue. A similar increase in stiffness has been reported for faster elbow movements

(Bennett et al., 1992; Silva et al., 2009). Thus, the increase in angular velocity of the spine reported here could indicate a movement strategy that would increase joint stiffness in order to overcome insufficient muscle stiffness due to changes in muscle physiology or insufficient passive stiffness due to creep in the passive structures during repetitive lifting activity.

More recently, Zuriaga et al., (2010) reported a delay in the feedback control of the trunk musculature with development of creep in the passive structures. The repetitive stooped postures observed while lifting in this study would have developed creep in the passive structures, which would increase the latency of the reflex response thereby leading to spinal instability (Moorhouse and Granata, 2007). Since faster movements

65 rely less on the feedback response for controlling the motion, participants would have adopted a strategy of faster movements in order to compensate for change in the biomechanical capacity of the trunk musculature. It is well documented that larger movement velocity increases the co-contraction from the antagonist abdominal muscles

(Marras and Mirka, 1993b; Dolan and Adams, 1993), which while providing increased stability (Granata and Marras 2000; Feltham et al., 2006), increases the biomechanical loads on spinal structures (Davis and Marras, 2000; Granata and England, 2006).

FEMAP

The flexion-extension motion assessment protocol was developed to assess whether prolonged repetitive lifting leads to deterioration in motor performance when performing a simple flexion-extension task. Our hypothesis was supported in that participants showed an increase in sagittal plane range of motion which corresponded to an overshoot of the targeted motion range. This result is in agreement with Kelaher

(2006), who showed an increase in trunk repositioning error in the sagittal plane following back muscle fatigue. A similar increase in sagittal plane range of motion has also been reported by Parkinson and colleagues (2004). Additionally, the increase in forward flexion is in accordance with the increase in the amount of forward bending flexion seen during the repetitive lifting task, suggesting development of creep in the passive structures of the spine such as discs and ligaments (Adams and Dolan, 1996) or the reluctance to eccentrically contract the erector spinae muscles to control the degree of forward flexion.

Although we expected to see an increase in the peak postural deviations in the coronal and axial planes based on Parnianpour et al.’s (1988) findings during a fatiguing back extension exertion task, our results did not support this hypothesis. However, we did find a significant increase in sagittal plane movement velocities and the twisting velocity. Fatigue in the erector spinae muscles due to repetitive lifting can take longer to generate the required force to control the motion during the FEMAP (Dolan and Adams

2001) which, along with creep in the passive structures, would indicate deterioration in the feedback response to control the motion (Zuriaga et al., 2010) and a reduction in passive stiffness of the spinal structures (Parkinson et al., 2004). In order to compensate for insufficient stiffness and delay in the neuromuscular response, participants could have adopted a strategy of faster movements which, while restoring spinal stability (Granata and Marras, 2000; Feltham et al., 2006), can increase spinal loading due greater co- activation of the trunk musculature (Davis and Marras, 2000; Granata and England,

2006).

There were some limitations that should be acknowledged concerning this study.

First, due to the exploratory nature of this study, we used a simple linear regression model to understand the behavioral and physiological responses to prolonged repetitive asymmetric lifting activity. Our data supports the use of this model especially for the participants who showed larger behavioral and physiological responses and also showed a stronger linear change as evidenced by the r-squared values in these relationships.

Second, we should recognize that all our participants were novice manual handlers from a university population, and previous studies have shown differences between experienced

67 and inexperienced lifters (Marras et al., 2006, Plamondon et al., 2012; Lee and Nussbaum

2012). One should be cautious in generalizing the results obtained from this study to experienced lifters. Third, the workplace layout was fixed in our study. Due to this, the relative work height and reach distance to the box would have varied with the anthropometric diversity in the sample. Fourth, the participants were restricted from lifting with their legs. This was done to limit the movement degrees of freedom to the spine and upper extremities. Clearly, the ability to increase the use of lower extremities in lifting could significantly alter the results found in this study.

2.5 Conclusions

In summary, prolonged repetitive asymmetric lifting led to decreases in tissue oxygenation measure along with increases in the subjective workload. Given that the spine kinematic measures which showed a significant change over the repetitive lifting task were also correlated with the decrease in oxygenated hemoglobin our results suggest that the behavioral responses due to repetitive lifting are likely associated with the development of muscle fatigue in the erector spinae muscles. These behavioral responses can increase back injury risk as the kinematic adaptations reported here have also been identified by lumbar motion monitor risk model (Marras et al., 1993) as factors for LBD risk, thereby providing some insight on the nature of elevated injury risk while performing repetitive asymmetric repetitive lifting tasks.

Chapter 3: Exploring Changes in Muscle Physiology and Lifting Behavior with

Combined Exposure to Whole Body Vibrations and Task Precision Demands

3.1 Introduction

Occupational driving and manual handling jobs have been associated with the development of low back pain (LBP) (Okunribido et al., 2008), suggesting that those who engage in both of these activities, for example, product or package delivery, may be at even greater risk due to their combined exposure to repetitive lifting tasks and whole body vibration (WBV). Moreover, manual handling tasks are often performed in asymmetric postures that require varying levels of task precision especially when loads are lifted from and/or placed on carts, hand trucks, or conveyors. Individually, physical factors such as repetitive work, vibration exposure, task precision demands, awkward postures etc, seen in delivery jobs have been associated with muscle fatigue and low back disorder (LBD) risk. Exposure to whole body vibrations has been associated with development of LBP (Cann et al., 2004; Robb et al., 2007; Okunribido et al., 2008) and lifting under high levels of task precision demands have been demonstrated to increase spinal loading (Davis et al., 2002; Beach et al., 2006). Even though combined exposure to vibration and manual handling tasks have been associated with the development of

LBP (Okunribido et al., 2008), no studies to my knowledge have looked at the interactive

69 effects of WBV exposure and manual handling task precision demands on measures of back injury risk.

The previous study (Chapter 2) demonstrated that repetitive asymmetric lifting activity leads to the development of localized fatigue in the erector spinae muscles which was seen as decrease in tissue oxygenation measures. Changes in the muscle physiology measures were also associated with behavioral changes during the repetitive asymmetric lifting task. Specifically, repetitive asymmetric lifting increased the amount of forward bending motion, and extension and lateral bending velocities of the spine, measures associated with increased risk to LBD.

The purpose of this study was to further explore and understand changes in lifting mechanics when repetitive asymmetric lifting activity is performed after exposure to

WBV and when lifting under high and low levels of task precision demands.

Specifically, to understand changes in muscle physiology, lifting behavior and motor performance measures when people are exposed to these physical risk factors in combination.

3.2 Methods

Experimental Design

This study was a 2 x 2 repeated measures design with two levels of vibration exposure (WBV and no-WBV) and two levels of lifting task precision demands (High and Low). Thus, each participant experienced the four combinations of the independent variables: (1) no-vibration – low task precision (NL), (2) WBV – low task precision

(VL), (3) no-vibration – high task precision (NH) and (4) WBV exposure – high task precision (VH). The sequence of these conditions were counterbalanced across participants and scheduled at least a week apart.

The dependent variables selected for this study were the same as those used in the prior study (chapter 2). This included assessment of changes in perceived exertion levels

(Borg), muscle physiology (oxygenated hemoglobin) and changes in movement behavior during the lifting task and the flexion-extension motion assessment protocol (FEMAP). In this study the FEMAP was performed in between every 20 minutes of the seated driving task and in between every 10 minutes of the repetitive lifting activity.

Sample

Seventeen healthy volunteers, thirteen males and four females between the ages of

18 and 32 (mean = 21.3 years, s.d. = 4.1 years) participated in the study. Mean height and weight of the participants were 1.76 m (s.d. = 0.07 m) and 79.7 kg (s.d. =11.2 kg).

Participants had no prior history of musculoskeletal disorders of the back, neck, shoulder, arms and legs within the past six months. All participants were recruited from university student population and had no experience in manual material handling jobs. All participants signed an institutional review board approved consent document prior to participating.

Procedures

Similar to Study 1, two NIRS sensors were placed over the participant’s erector spinae muscles (L3 level) to assess changes in tissue oxygenation. Eleven motion monitor sensors were attached to each participant to capture the lifting behaviors. The

Borg scale rating was used to quantify subjective perception of the overall workload. A more detailed description can be obtained in Chapters 4 and 5.

Prior to the lifting task, participants were seated on a vibration platform without back support for 60 minutes (driving task). In the VL and VH conditions, participants were vibrated at frequency of 5 Hz (sinusoidal vibrations) and vertical acceleration levels of 0.1g. In the no-vibration sessions (NL and NH), participants sat on the same seat as that used during the WBV sessions for the same amount of time. In both the WBV and no-vibration condition, participants interacted with a driving simulator. Every 20 minutes, in both the vibration exposure and no-vibration condition participants were asked to perform the FEMAP and a Borg rating was obtained. After 60 minutes of driving (WBV or non-vibration), the lifting task began.

The lifting protocol was similar to that described in Study 1 (Chapter 2).

Depending on the session (low or high precision demands) for that day, the guide rails on the destination conveyor were adjusted to the high or low task precision demand position.

For the low precision demand condition, there was 0.1m side to side space between the box and the guide rails. Conversely, for the high task precision demands this space was narrowed to 0.006m. The vertical clearance for both task precision demands remained the same (0.02m). The task was comprised of six 100-lift blocks where the lifts were paced at

10 lifts/minute for 10 minutes. An auditory cue signaled when lifts should be initiated.

At the end of each 10-minute lifting period, the lifting was interrupted for approximately a minute as a FEMAP was performed and a Borg scale rating was obtained.

The FEMAP was the same as used in study 1 where participants performed 8 flexion-extension tasks from an upright standing posture to their two-thirds range of motion in the sagittal plane. An auditory cue signaled when the participant had flexed or extended the appropriate amount.

Data Analysis

The data obtained from the dependent measures (Borg, muscle physiology and spine kinematics during the FEMAP) were separately analyzed for the simulated driving and the lifting task. All the dependent measures were analyzed using a within subjects repeated measures ANOVA procedure using IBM SPSS (version 19). For the participants who were not able to complete the 60 minutes of the repetitive lifting task (N

= 3), a conservative imputation approach of carrying their last measured value forward was used so they could be included in the ANOVA procedures. A paired t-test comparison was conducted when significant interactions were obtained between the independent variables. In all statistical tests, a p-value<0.05 was considered to be statistically significant.

3.3 Results

Overall Subjective Workload (Borg rating)

Table 1 below shows the results from a repeated measures ANOVA for the driving and the lifting task. Overall, Borg ratings of perceived exertion increased significantly over time during the 60 minutes of the driving and the lifting task. During the driving task, Borg ratings were significantly higher when participants were exposed to WBV (1.54) as compared to quiet sitting (1.14). However, no significant interaction between vibration exposure and task precision demands was observed during the repetitive lifting task.

Table 1: p-values for the rating of perceived exertion (RPE) during the driving and the repetitive lifting phases of the experiment (bold text indicates p<0.05).

Borg RPE Phase of Experiment Driving Lifting Vibration (V) 0.019 0.817 Demands (D) 0.205 0.577 Time (T) <0.001 <0.001 V x D 0.760 0.766 V x T 0.136 0.883 D x T 0.826 0.704 V x D X T 0.418 0.569

Muscle Physiology (oxygenated hemoglobin levels)

Oxygenated hemoglobin levels obtained from the NIRS system decreased significantly over time during the driving and the lifting task (Table 2). Exposure to

WBV and task precision demands showed no main effect or interaction with this measure.

Table 2: p-values for the right oxygenated hemoglobin levels during the driving and lifting task (bold text indicates p<0.05).

Tissue Oxygenation Phase of Experiment Driving Lifting Vibration (V) 0.495 0.975 Demands (D) 0.172 0.935 Time (T) <0.001 <0.001 V x D 0.754 0.567 V x T 0.640 0.912 D x T 0.357 0.794 V x D X T 0.763 0.812

Lifting Task

During the 60 minutes of the repetitive asymmetric lifting activity, forward bending and lateral bending motions of the spine, along with three dimensional movement velocities increased significantly over time (Table 3). The lateral bending moment of the spine and lift duration decreased with repetitive lifting activity.

Table 3: p-values for the spine kinematic and moment measures during the lifting task (bold text indicates p<0.05).

Flex Twist Lateral Forward Twisting Lateral Extension Twisting Lateral Lift Lifting Bend Bending Moment Bending Velocity velocity Bending Duration Moment Moment Velocity

Vibration (V) 0.609 0.040 0.178 0.780 0.357 0.870 0.481 0.216 0.708 0.417

Demands (D) 0.995 0.079 0.941 0.927 0.389 0.017 0.059 0.178 0.699 0.029

Time (T) <0.001 0.446 0.028 0.184 0.052 <0.001 <0.001 <0.001 <0.001 <0.001

V x D 0.229 0.210 0.028 0.165 0.640 0.130 0.867 0.016 0.241 0.723

V x T 0.592 0.656 0.158 0.932 0.815 0.418 0.628 0.979 0.760 0.540

D x T 0.631 0.402 0.778 0.095 0.069 0.907 0.051 0.822 0.958 0.525

VxDxT 0.997 0.402 0.528 0.478 0.25 0.981 0.925 0.020 0.797 0.969

Twisting motions were significantly higher when participants were exposed to

WBV (27.1 degrees) as compared to lifting that followed quiet sitting (25.1 degrees).

Task precision demands significantly affected the lateral bending moment of the spine.

Specifically, lifting under high precision demands led to significantly greater lateral bending moments (82.8 Nm) as compared to lifting under low demands of task precision

(75.2 Nm). Moreover, lifts performed under high demands of task precision (2.1 seconds) took significantly longer than low demands of task precision (1.9 seconds).

Lateral bending motion of the spine showed a significant interaction effect between task precision demands and vibration exposure (Table 3). Specifically, when lifting under low precision demands, the amount of lateral bending was significantly smaller when lifting task was performed after exposure to WBV (p < 0.05). Additionally, when exposed to WBV, the amount of lateral bending motion was larger when lifting task was performed under high demands, whereas, an opposite trend was observed when lifting task was performed after quiet sitting (Figure 13).

14 * 12 10 8 Vibration 6 No-Vibration 4 2 0

lateralbending motion(degrees) Low High Task Precision Demands

Figure 13: Vibration x Task Precision Demand interaction for lateral bending motions of the spine (“*” indicates p < 0.05).

A three-way interaction between exposure, task precision demands and time for spine twisting velocity is shown in Figure 14. Specifically, twisting velocity during lifting under high precision demands after exposure to WBV (VH), along with no- vibration and lifting under low demands (NL) showed a significant increase over time (p

< 0.01). Whereas, lifting under low demands after exposure to WBV (VL), and lifting under high demands after quiet sitting (NH) showed no change in twisting velocity over time (p > 0.05). During the final 10-minute block of lifting, twisting velocity of the spine under the VH condition was significantly greater as compared to rest of the experimental conditions (p < 0.05).

* )

2 70 60 50 40 30 VL VH 20 NL

Twistingvelocity (m/s 10 ND 0 10 20 30 40 50 60 Time (minutes)

Figure 14: Three-way interaction between Vibration, Task Precision Demands and Time for twisting velocity of the spine (“*” indicates p < 0.05)

FEMAP

During the simulated driving task, spine kinematic variables (forward bending motion, and three-dimensional movement velocities) increased significantly over time

(Table 4). However, exposure to WBV and task precision demands showed no significant effect or interaction on any of the spine kinematic measures.

Table 4: p-values for the spine kinematic measures during the driving task for the FEMAP (bold text indicates p<0.05).

Driving Flexion Twisting Lateral Forward Extension Twisting Lateral Bending Bending Velocity Velocity Bending Velocity Velocity Vibration (V) 0.467 0.778 0.915 0.920 0.791 0.086 0.763 Demands (D) 0.071 0.056 0.891 0.843 0.669 0.199 0.479 Time (T) 0.009 0.352 0.678 0.024 <0.001 0.003 <0.001 V x D 0.092 0.821 0.704 0.790 0.482 0.497 0.444 V x T 0.256 0.119 0.137 0.256 0.481 0.615 0.977 D x T 0.306 0.783 0.063 0.889 0.642 0.896 0.817 V x D X T 0.987 0.412 0.448 0.534 0.947 0.241 0.322 78

Spine kinematic variables (motions and velocities) in all three planes of motions increased significantly over time during the FEMAP performed in between the repetitive lifting activity (Table 5).

Table 5: p-values for the spine kinematic measures during the lifting task for the FEMAP (bold text indicates p<0.05).

Lifting Flexion Twisting Lateral Forward Extension Twisting Lateral Bending Bending Velocity Velocity Bending Velocity Velocity Vibration (V) 0.827 0.773 0.753 0.805 0.588 0.904 0.675 Demands (D) 0.237 0.075 0.162 0.685 0.788 0.230 0.757 Time (T) <0.001 0.007 0.003 <0.001 <0.001 0.001 <0.001 V x D 0.034 0.764 0.680 0.287 0.671 0.224 0.425 V x T 0.941 0.896 0.721 0.616 0.701 0.042 0.505 D x T 0.377 0.407 0.492 0.143 0.516 0.828 0.574 V x D X T 0.533 0.867 0.778 0.582 0.917 0.464 0.052

A significant interaction between task precision demands and vibration exposure was observed for the amount of spine flexion (Table 5 and Figure 15). When exposed to

WBV, the amount of forward bending for lifts performed under high task precision demands were significantly greater than lifts performed under low precision demands (p

= 0.013), whereas, no significant difference was observed between low and high demands for lifting activity performed after quiet sitting (p = 0.253).

45 40 35

30 25 Vibration 20

(degrees) 15 No-Vibration 10 5 ForwardBending Motion 0 Low High Task Precision Demands

Figure 15: Vibration x Task Precision Demand interaction for forward bending motions of the spine

A significant interaction between vibration exposure and time for the spine twisting velocity is shown in figure 16. The spine twisting velocity increased significantly over time when lifting activity was preceded by WBV (p < 0.05); whereas no change in this measure was observed for lifting task preceded by quiet sitting.

Additionally, the differences were statistically significant only after the last 10 minutes of repetitive lifting activity (p = 0.03).

40 * 35 30 25 20 Vibration 15 No-vibration 10

5 Twisting Twisting Velocity (degrees/sec) 0 10 20 30 40 50 60 Time (minutes)

Figure 16: Vibration x Time for twisting velocity of the spine during the FEMAP (“*” indicates p<0.05)

3.4 Discussion

Results obtained from this study validate the findings from study 1 (chapter 2) that showed subjective (Borg) and objective (oxygenated hemoglobin) measures of muscle fatigue to increase with repetitive asymmetric lifting activity. During the driving phase of the experiment, vibration exposure only affected the Borg ratings; suggesting higher physiological demands (Capodaglio, 2001; Coutts et al., 2009) and fatigue development (Kimura et al., 2007; Hummel et al., 2005; Looze et al., 2009) with exposure to WBV as compared with unsupported sitting.

During the repetitive lifting activity, spine kinematic and moment measures showed similar effects to those seen in study 1. Specifically, the amount of forward bending and the three-dimensional movement velocities of the spine increased over time; whereas, the lateral bending moment and the lift duration decreased with repetitive lifting activity. In addition to the overall changes, the amount of twisting was significantly 81 higher when participants were exposed to WBV prior to engaging in the lifting task. The larger twisting motions seen following exposure to WBV can increase rotational creep of the spine (Shan et al., 2013), as well as increase co-contraction of the trunk musculature

(Lavender et al., 1993; Marras and Granata, 1995b) and thereby increase spinal loading

(Granata and Marras, 1995).

Even though there was an overall decrease in the lateral bending moment of the spine and the overall lift duration, high levels of task precision led to significantly larger lateral bending moment and longer lift durations as compared to lifting under low demands. There is evidence to suggest that higher levels of lateral bending moment increase LBD risk (Marras et al., 1993). The longer lift duration in performing high precision lifting task could also increase the risk to back injury as strong association have been identified between lift duration and the risk to back injury (Marras et al., 2010).

All this evidence suggests behavioral changes associated with exposure to WBV prior to engaging in lifting tasks and lifting tasks that require more precision further increase the risk to LBD. With the exception of twisting velocity, no interaction was observed between vibration exposure and task precision demands over the repetitive asymmetric lifting activity.

FEMAP performed in between the repetitive asymmetric lifting activity showed larger movements in all planes of motion over time. These results are in support of

Parnianpour et al. (1988) that reported larger out-of-plane movements following back muscle fatigue. The increased out-of-plane movements indicate deterioration of motor performance during the repetitive lifting activity. In order to preserve the overall task

82 performance and maintain spinal stability following muscle fatigue, the central nervous system would have recruited the antagonist abdominal muscles (Reeves et al., 2008), in addition to fatiguing back extensor muscles to increase joint stiffness, when performing the flexion-extension task; this increase in co-contraction can impose additional loads on the spine (Granata and Marras, 1995).

The hypotheses outlined in chapter 1 suggested the expectation of larger changes in muscle physiology and movement behavior when participants were exposed to a combination of WBV prior to lifting and high task precision demands. However, this hypothesis was not supported. Instead, these results suggest that the combined exposure to WBV prior to lifting and task precision demands may not have additive or multiplicative effect on muscle physiology, lifting behavior, and motor performance measures. To further explore the individual contribution of vibration exposure and precision demands on the repetitive lifting task, the data have been analyzed separately for the vibration exposure conditions (under high precision demands – Chapter 4) and task precision demands conditions (lifting preceded by quiet sitting – Chapter 5) to better understand the back injury risk associated with these potential occupational risk factors for low back pain.

Chapter 4: Exploring the Effects of Seated Whole Body Vibration Exposure on

Repetitive Asymmetric Lifting Tasks

4.1 Introduction

In 2012, Bureau of Labor Statistics (BLS) reported employment in transportation and material moving occupations may increase by 20% from 2010 to 2020 (BLS, 2012).

The predicted increase comes with the advancement of technology and e-commerce where there is an increasing demand for goods to be distributed at a faster rate.

Individually, exposure to physical factors such as repetitive work and whole body vibration (WBV) seen in these occupations have been associated with low back pain

(LBP) (Hoogendorn et al., 1999; NRC, 2001), suggesting that those who engage in both of these activities, for example, product or package delivery, may be at even greater risk due to their exposure to repetitive lifting tasks and WBV.

Research has shown that WBV exposure to vibrations frequencies between 4.5 -

8Hz increases the risk of low back disorders (LBD) and causes degenerative changes in the spinal system (Bovenzi et al., 1999). Epidemiological studies have identified a strong association between occupational driving and risk of low back pain. Specifically, truck drivers, tractor drivers, bus drivers, taxi drivers and earth equipment movers have high risk of LBP (Cann et al., 2004; Robb et al., 2007; Okunribido et al., 2008). In the animal literature there is direct evidence to suggest disc degeneration after exposure to vibrations

(Ekstrom et al., 1996; Yamazaki et al., 2002; Gregory et al., 2011). In humans, exposure to WBV can affect neuromuscular control of the human spine. This has been reported as creep in the passive structures of the spinal system (Sullivan and McGill 1990;

Magnusson et al., 1992) and increased delay in the feedback control of the neuromuscular response (Wilder et al., 1996; Li et al., 2008). As compared to seating without vibration, studies have also reported development of back muscle fatigue with exposure to 5 Hz

WBV (Hansson et al., 1991; Pope et al., 1998). These changes in the neuromuscular control due to seated WBV exposure can have implications on spinal stability (Panjabi,

1992) and thereby increase the risk of back injury.

Epidemiological studies have also indicated that exposure to WBV is often accompanied by manual handling tasks (Punnett et al., 2005; Okunribido et al., 2008).

The association between manual material handling tasks and LBP is well established

(Macfarlane et al., 1997; Hughes et al., 1997; Vandergrift et al., 2012; Lavender et al.,

2012). More specifically, manual handling tasks that involve repetitive bending, twisting, carrying or lifting movements have been associated with LBP (Marras et al.,

1993; Heneweer et al., 2011; Mikkonen et al., 2012; Lavender et al., 2012). In addition, repetitive lifting during manual handling tasks has been associated with muscle fatigue

(Dempsey, 1998). Muscle fatigue induced due to repetitive trunk movements can affect neuromuscular control of the spine (Parnianpour et al., 1988; Kroemer 1992; Mawston et al., 2007; Granata and Gottipati, 2008). Thus, the increased rate of muscle fatigue with

WBV exposure is thought to increase the rate of fatigue during the lifting components of these jobs and therein, by the yet to be determined mechanism, increase LBD risk.

In compensating for muscle fatigue during a repetitive lifting task, studies have shown that people adapt their working strategy resulting in larger behavioral changes.

During repetitive symmetric lifting tasks this has been seen as alternation between stoop and squat postures (Trafimow et al., 1993; van Dieen et al., 1998; Chen 2000; Bonato et al., 2003) and between trunk and hip kinematics (Sparto et al., 1997; Marras and Granata,

1997). Behavioral adaptations during a repetitive asymmetric lifting task have been seen as increase in the amount of forward bending of the spine when initiating lifts and an increase in the lateral bending velocity (Mehta et al., 2014) both of which are behaviors identified by the Lumbar Motion Monitor model to increase LBD risk (Marras et al.,

1993).

Recently, near-infrared spectroscopy (NIRS) has been used to quantify changes in the muscle physiology (McGill et al., 2000; Hamaoka et al., 2007). There is direct evidence to suggest the link between tissue oxygenation levels (as measured by NIRS) and localized muscle fatigue (Ferguson et al., 2013). Specifically, studies have shown high correlations between changes in median frequency response of the electromyographic signals and physiological measures obtained from the NIRS system

(Miura et al., 2000; Yamada et al., 2008; Ferguson et al., 2013). Decrease in tissue oxygenation levels during seated WBV exposure has been demonstrated by Maikala and

Bhambhani (2006 and 2008). In our prior work, we have shown changes in erector spinae muscle physiology with repetitive asymmetric lifting task (Mehta et al., 2014).

The aim of this research was to determine if the behavioral and physiological changes associated with repetitive asymmetric lifting tasks are more pronounced when

86 the lifting is preceded by WBV exposure. Relative to lifting tasks that are not preceded by WBV, repetitive asymmetric lifting activity preceded by WBV exposure is hypothesized to (1) accelerate the decrease in tissue oxygenation in the back muscles; (2) lead to a more rapid increase in sagittal plane range of motion while performing a controlled spine flexion-extension motion protocol; (3) result in more frequent and pronounced compensatory behaviors during a defined lifting task as measured by increases in spine kinematic measures; and (4) increase biomechanical loading of the spine.

4.2 Methods

Experimental Design

This research is part of a larger study investigating the effects of vibration exposure and lifting task precision demands on biomechanical changes experienced during a repetitive lifting task. Since our initial analyses indicated that there were no significant interactions between the lifting precision demands and the vibration exposure conditions, this paper is focused on analyzing the effects of repetitive lifting under the high task precision demands condition that is preceded by a simulated driving task which was performed with and without WBV. The repeated measures design counterbalanced the sequences of WBV exposure and were scheduled at least a week apart. For each of the experimental conditions, participants lifted a box (15% of their maximum capacity) repetitively over a 60 minute period using a stoop posture.

The dependent variables were selected to assess changes in the physiological and behavioral responses. During the 60-minute simulated driving task and the 60-minute repetitive asymmetric lifting task, changes in muscle physiology were assessed using hemoglobin levels derived from the Near Infrared Spectroscopy (NIRS) signals.

Subjective workload was evaluated using a self report measure (Borg CR-10 scale).

Behavioral and biomechanical changes during the repetitive lifting task were assessed using measures of lift duration, three-dimensional spine kinematics between (T1 and S1) and three-dimensional spine moments. In addition, three-dimensional peak motions were evaluated during a flexion-extension motion assessment protocol (FEMAP) to evaluate changes in motor performance during the simulated driving and repetitive lifting tasks.

Sample

Seventeen healthy volunteers, thirteen males and four females between the ages of

18 and 32 (mean = 21.3 years, s.d. = 4.1 years) participated in the study. Mean height and weight of the participants were 1.76 m (s.d. = 0.07 m) and 79.7 kg (s.d. =11.2 kg).

Apparatus

A custom built WBV platform was designed and developed for this study (Figure

17a). The seated participants were vibrated at a frequency of 5 Hz (sinusoidal vibrations) and vertical acceleration levels of 0.1g as they performed a simulated driving task. The seat did not have a back support.

Figure 17: Experimental setup during the simulated driving task (a) and the lifting task (b)

0.006m side to side space between the box and the guide rails, and a vertical clearance of

0.02m. The wooden box (0.4 x 0.3 x 0.25m) lifted by the participants had handles and was filled with reams of paper to the desired weight.

Self report measures (Borg CR-10 scale, Borg, 1982) were obtained to quantify changes in the overall subjective workload during the seating and the repetitive lifting task. Near-Infrared Spectroscopy (NIRS) was used to evaluate changes in muscle physiology during the 60 minutes of simulated driving and the 60 minutes of lifting activity. The NIRS system provides a direct measurement of oxygen delivered and utilized at the muscle site. Sensors from the two-channel INVOS 4100 Cerebral

Oximeter (Somanetics Corporation, Troy, MI, USA) were attached over the erector spinae muscles at the L3 level.. Changes in total, oxygenated and deoxygenated hemoglobin levels were continuously monitored at 85 Hz. Previously, studies have demonstrated oxygenated hemoglobin levels to be more sensitive in detecting physiological changes repetitive work (Ferguson et al., 2013; Mehta et al., 2014), thus, this is the NIRS measure used in this paper.

Three-dimensional spine motions were captured (at 120 Hz) using a magnetic motion capture system (The Motion Monitor TM, Chicago, IL) to assess spine kinematic

90 changes associated with the repetitive asymmetric lifting task and performance changes during the FEMAP performed periodically throughout the data collection process.

Bertec force plates were used to measure ground reaction forces that provided input into a three-dimensional dynamic linked-segment model within the Motion Monitor System that computes the three-dimensional moments acting at L5/S1. Two Inscale (Terra Haute

Indiana) force scales, positioned beneath the conveyors, were used to identify the timing of the initial lift and the box placement in the data stream collected during the lifting task.. Maximum lifting strength, used to scale the box weight for each individual participant’s capability, was measured using a dynamometer.

During 60 minutes of the simulated driving task, participants interacted with the

Scania Truck Driving Simulator (SCS Software). The driving controls included a steering wheel with integrated pedals mounted in front of the vibrating platform (Racin’

Pro, SubsonicTM). The steering wheel and pedal assembly was adjusted to each participants’ desired driving position.

Procedures

At the beginning of each participant’s first experimental session, lifting strength was assessed using a maximum isometric assessment in which the participant attempted to pull upwards on a handle located at the same height and distance from the ankles as the handles on the box during initial part of the lifting task. The box weight which was adjusted to 15% of each individual subject’s maximum lifting strength (indicated by the larger of the two exertions). On average, the box weighed 11.06 kg (s.d. = 3.53 kg).

Eleven motion capture system sensors were attached to the participants at the following locations: on top the head, at the top of the thoracic spine (T1), over the top of the sacrum (S1), and bilaterally on the upper and lower arms and legs. Additionally, the two NIRS sensors were placed bilaterally on the erector spinae muscles at the L3 level.

Prior to beginning each session, the participant’s maximum range of motion

(ROM) in the sagittal plane was measured. With eyes closed, participants were asked to bend forward maximally to obtain each individual’s maximum trunk flexion capacity.

60-minute Simulated Driving Period

Prior to the lifting task in each session, the participants performed the simulated driving task during which they were seated on the vibration platform for 60 minutes without back support. Prior to one driving session, the platform was turned on, therein exposing the participants to vibration and in the other session, the participants sat on the same platform for the same amount of time but it did not vibrate. The participants were instructed that they were not judged on their driving ability. Before beginning the 60- minute driving period, and every 20 minutes thereafter, the participants performed the

Flexion-Extension Motion Assessment Protocol (FEMAP).

The Lifting Task

The participants repetitively lifted the box from a conveyor in front of them (0.25m above the floor) using the handles to the conveyor located to their left side (0.86m above floor) without moving their feet and while using primarily a stoop posture. The task was

92 paced so that the participants performed 10 lifts/minute for 10 minutes. An audio signal, provided every six seconds, indicated when each lift should be initiated. At the end of each

10-minute lifting period, the FEMAP (described below) was performed, and a Borg scale rating was obtained, after which another 10-minutes of lifting was initiated. This process of lifting for 10 minutes, followed by FEMAP continued until 60 minutes of lifting was completed or until the participant indicated they were fatigued and were no longer able to continue. Where participants terminated their lifting before the end of the 60-minute period, a final FEMAP was performed and a Borg rating was obtained. Participants were given an opportunity to practice the lifting task before starting the first 10-minute block of lifts.

Flexion-Extension Motion Assessment Protocol (FEMAP)

A protocol was developed to periodically evaluate trunk kinematic performance at selected points during the subject’s participation in the experiment. This protocol was conducted at the beginning of the 60-minute driving tasks and every 20 minutes thereafter. Once the lifting task was initiated, the FEMAP was conducted in between each 10-minutes of the lifting activity (Mehta et al., 2014). In this procedure, the participant, with eyes closed, repeatedly flexed forward to a target position that was defined as two-thirds of their maximum trunk flexion capacity as fast as they could and returned to an upright standing posture. These motions were repeated 10 times during which spine kinematic data were collected. Spine position information was provided via auditory feedback in that an auditory tone signaled when participants reached the target position and when they returned back to their upright standing posture. Prior to the first

93 experimental session, participants were allowed to practice the flexion-extension task till they felt comfortable with this procedure.

Data Analysis

Self report scores obtained from Borg scale ratings were used to identify changes in the overall subjective workload during the 60 minutes of simulated driving and the 60 minutes of repetitive lifting activity. For the muscle physiology measure, the average of the each 20-minute period of the driving task and 10-minute period of the lifting task was calculated. While the simulated driving data were normalized to baseline values (Mehta et al., 2014), the lifting data were normalized to the initial 10 minutes of the lifting activity.

To assess behavioral and biomechanical changes during the prolonged lifting task, the peak three dimensional spine kinematics and moments were obtained for each lift. The timing of the individual lifts was calculated based on the force scale data. Means of the duration data, peak kinematic and moment measures for each 10 minutes of lifting activity were computed to identify parameters indicative of behavioral and biomechanical adaptations during lifting. For each flexion-extension movement task during the FEMAP, three- dimensional peak displacements and movement velocities were obtained.

The resulting data from the NIRS and motion monitor system measures were analyzed using a within subjects repeated measures ANOVA procedure using IBM SPSS

(version 19). Due to the difference in the nature of the task between seating and lifting, the Borg, NIRS and the FEMAP measures were separately analyzed for the 60 minutes of simulated driving and the 60 minutes of repetitive lifting. For the participants that were

94 not able to complete 60 minutes of repetitive lifting (N = 3, one session each), we used a conservative imputation approach of carrying their last measured value forward so they could be included in the ANOVA procedures. A paired t-test comparison was conducted when significant interactions were obtained between vibration exposure and time. In all statistical tests, a p-value <0.05 was considered to be statistically significant.

4.3 Results

Overall subjective workload

Figure 18 shows the changes in the Borg ratings of perceived exertion (RPE) over time during the 60-minutes of simulated driving and the lifting tasks. During 60 minutes of simulated driving and the 60 minutes of lifting, the RPE increased significantly over time (p< 0. 001). However, vibration exposure showed no significant effect or interaction with time during the seated driving period or during the lifting activity (p >

0.05).

Muscle physiology measures

Oxygenated hemoglobin levels were used to quantify changes in the erector spinae muscle physiology. Oxygenated hemoglobin levels from the left and right erector spinae muscles were highly correlated (r > .92) in both the vibration and no-vibration conditions. Considering the high correlations between the left and right erector spinae muscles, further results focus on the changes oxygenated hemoglobin levels measured on the right side.

Figures 19a and 19b show percent change from baseline in the levels of oxygenated hemoglobin derived from the NIRS system decreased significantly over time

(p<.0001) during the simulated driving and the lifting tasks. During the lifting task, the oxygenated hemoglobin levels decreased significantly for the initial 30 minutes of the repetitive lifting task after which no change was observed for this physiological measure.

WBV exposure prior to the lifting task did not affect these changes in oxygenated hemoglobin levels (p > 0.05).

Figure 19: NIRS - Vibration x time interaction for the oxygenated hemoglobin levels obtained from the NIRS system during the simulated driving (a) and the lifting task (b). Vertical bars indicate standard error of the mean

Behavioral changes with repetitive lifting

The overall lift duration during the repetitive asymmetric lifting task decreased significantly over time (p < 0.001). This trend was linear (r2 = 0.72) with an average decrease of 0.02 seconds with every 10 minutes of repetitive lifting activity. Exposure to

WBV did not change the overall lift duration.

Figure 20 shows changes in the three-dimensional spine motions over time during the repetitive asymmetric lifting tasks. The amount of spine flexion increased significantly over time (p = 0.016). A post-hoc analysis showed that the magnitude of the forward bending during the last 10 minutes of repetitive lifting task was significantly greater than that observed during the initial 10 minutes of the repetitive lifting task.

WBV exposure showed no effect on this measure. The amount of spine twisting motion during the repetitive lifting task after exposure to whole body vibration (28.8o) was significantly greater (p = 0.046) than when lifting followed the driving without WBV

(25.4o). However, there were no trends in the overall twisting motions across the 60- minutes of lifting. Lateral bending motions of the spine were unaffected by either the repetitive lifting or the exposure to WBV (p > 0.05).

Changes in three-dimensional spine moments during the repetitive asymmetric lifting task are shown in Figure 21. Overall, forward bending moment acting on the spine was unaffected by the repetitive lifting activity (p < 0.05). While the twisting moment acting on the spine increased significantly over time (p = 0.012), the lateral bending moment on the spine decreased significantly over time (p < 0.001). Exposure to WBV showed no effect on the moment measures.

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The three-dimensional movement velocities of the spine increased significantly (p <

0.01) over time (Figure 22). Post-hoc analyses showed that for the extension and twisting velocities, the changes in these measures occurred only when the lifting was preceded by exposure to WBV (Figure 22a and 22b). In addition to the time dependent effects, when the lifting followed WBV exposure there were larger (p = 0.025) twisting velocities (62 degrees/sec) than when the lifting followed the driving without WBV (56.9 degrees/sec).

As for the lateral bending velocity, a post-hoc analysis indicated that only the driving without vibration condition significantly increased the lateral bending velocity (Figure

22c).

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Flexion-Extension Motion Assessment Protocol (FEMAP)

FEMAP results from the Driving Task

The three-dimensional spine kinematics variables that showed a significant main effect over time during the seated driving task are shown in Figure 23. On average, the peak sagittal plane range of motion increased significantly over time (p = 0.047). The twisting and lateral bending ROM were unaffected by WBV or the repetitive lifting task

(p > 0.05). Peak forward bending, extension and lateral bending velocities of the spine increased significantly over time (p < 0.05); whereas twisting velocity showed a marginal increase over time (p = 0.061) while performing the driving task.

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FEMAP results obtained during the Lifting Task

Figure 24 shows the peak sagittal plane range of motion during the lifting task as a function of vibration exposure. The peak deviations in the sagittal plane increased significantly over time (p = 0.003). However, the peak deviations in the axial and coronal planes were not affected by the repetitive lifting activity. WBV exposure prior to lifting did not affect the spine ROM and showed no significant interaction during the

FEMAP.

50 45 40 degrees 35 30 10 20 30 40 50 60 Time (minutes)

Figure 24: FEMAP - Vibration x time interaction for peak range of motion in sagittal plane during the lifting task. Vertical bars indicate standard error of the mean

Three dimensional movement velocities of the spine during the lifting task are shown in Figure 25; here, movement velocities increased significantly over time during the FEMAP (p < 0.05). A marginal interaction between vibration exposure and time (p =

0.069) suggests that the overall increase in twisting velocity was potentially due to the vibration exposure prior to the lifting task (Figure 25c). 107

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4.4 Discussion

The purpose of this study was to understand the sequential effects of seated WBV exposure on the repetitive asymmetric lifting activity. Overall, exposure to WBV showed no significant effect on the ratings of perceived exertion and muscle physiology measures during the 60 minutes of simulated driving and during the repetitive asymmetric lifting task. As for behavioral measures, repetitive asymmetric lifting activity preceded by

WBV exposure resulted in significantly larger twisting motions and twisting velocities of the spine.

Changes in the Overall Subjective Workload

Our results showed that the overall subjective workload increased significantly over time during the 60 minutes of the simulated driving and the repetitive asymmetric lifting activity. These results are similar to other studies in the literature that have shown increase in Borg rating of perceived exertion during the repetitive lifting tasks (Garg and

Banaag, 1988; Bonato et al., 2003; Lotz et al., 2009). Increase in perceived physical effort over time has been shown previously to be associated with the development of muscle fatigue (Dedering et al., 1999; Kimura et al., 2007; Hummel et al., 2005; Looze et al., 2009). However, exposure to WBV showed no effect on the overall subjective workload; indicating that this subjective measure of fatigue is largely affected by the prolonged seating and lifting activity independent of the vibration exposure.

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Changes in Muscle Physiology Measures

Tissue oxygenation measures obtained from the NIRS system were used to quantify changes in the erector spinae muscle physiology. Overall during the simulated driving and the repetitive lifting task, the oxygenated hemoglobin levels decreased significantly over time. Previously, studies have shown development of muscle fatigue, as measured with EMG spectral analysis, is associated with decrease in oxygenated hemoglobin levels (Miura et al., 2000; Yamada et al., 2008; Ferguson et al., 2013).

Thus, the decrease in oxygenated hemoglobin levels during the simulated driving and the repetitive asymmetric lifting activity is indicative of fatigue development in the erector spinae muscles.

Our hypothesis that the exposure to WBV would lead to a larger decrease in the tissue oxygenation measures was not supported. As such, our results are in disagreement with the prior studies that have shown erector spinae fatigue with seated WBV exposure

(Hansson et al., 1991; Pope et al., 1998). In their studies, participants were holding an extra weight and were seated with trunk flexed forward (Hansson et al., 1991; Pope et al.,

1998). These variations would further engage the back extensor muscles and potentially enhance fatigue development. Studies that have looked at a more realistic scenario have found similar effects of WBV exposure and quiet sitting on back muscle fatigue measures as seen in the current study (El Falou et al., 2003; Santos et al., 2008). It is possible that exposure to WBV increased the amount of co-contraction from the trunk musculature, thereby fatiguing the abdominal muscles in addition to the fatiguing back extensor muscles. In our study we did not measure abdominal muscle physiology; perhaps

110 measurement of the abdominal muscle physiology would provide insight to the level of co-activity after exposure to WBV.

Behavioral changes after exposure to WBV

The amount of twisting and the twisting velocity of the spine during the repetitive asymmetric lifting tasks were significantly higher when participants were exposed to

WBV. Exposure to WBV has been known to affect neuromuscular control of the spine.

Specifically, studies have reported increased latency in the feedback response after exposure to seated WBV (Wilder et al., 1996; Li et al., 2008; Arora and Grenier, 2013).

Thus, the larger twisting motions and movement velocity after exposure to WBV could be a coping strategy to compensate for the poor feedback response in controlling the precise motions during box placement. Larger twisting motions seen during WBV exposure can cause rotational creep of the spine (Shan et al., 2013), thereby increasing the risk of injury to the passive stabilizing structures. In their lumbar motion monitor model, Marras et al. (1993) identified twisting velocity as one of the key factors used to determine LBD risk. Both the amount of twisting and the velocity of twisting have been reported to increase coactivity from the trunk musculature (Marras and Granata, 1995 and

1997), and increased co-contraction has been demonstrated to increase LBD risk (Granta and Marras, 1995).

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Behavior changes associated with time

Behavioral changes reported here are similar to the results obtained in our prior work (Mehta et al., 2014). In this study, twisting moments typically peaked while picking the boxes in a flexed posture. One of the tissues under strain in the stooped posture from which the lifts originated is the annulus fibrosis which is not well suited to resist large twisting moments. Thus, the increase in twisting moments along with simultaneous forward bending motions would increase the increase the risk of low back injury (Duncan and Ahmed, 1991). Further, three of the five factors (forward flexion, twisting velocity and lateral bending velocity) that changed over time with the repetitive lifting activity have also been shown to increase the risk of back injury (Marras et al.,

1993).

FEMAP

The flexion-extension motion assessment protocol was developed to test whether prolonged repetitive asymmetric lifting that was preceded by whole body vibration exposure leads to deterioration in motor performance when performing a simple flexion- extension task. Our hypothesis was partially supported in that participants showed an increase in the sagittal plane range of motion during the simulated driving and the lifting tasks. Larger deviations of the spine in the sagittal plane suggest creep in the passive structures of the spine (Adams and Dolan, 1996) or a change in the neuromuscular response. However, the lack of differences between the vibration conditions suggest that

112 it is the lifting task, rather than the vibration exposure that is not contributing to this increased motion in the sagittal plane.

There were some limitations that should be acknowledged concerning this study.

First, we should recognize that all our participants were novice manual handlers from a university population, and previous studies have shown differences between experienced and inexperienced lifters (Marras et al., 2006; Plamondon et al., 2012; Lee and

Nussbaum, 2012). One should be cautious in generalizing the results obtained from this study to experienced lifters. Second, the participants were not provided a backrest during the seating task. Addition of a backrest would substantially change the transmission of vibrations to the human body (Hinz et al., 2002). Third, the workplace layout was fixed in our study. Due to this, the relative work height and reach distance to the box would have varied with the anthropometric diversity in the sample. Fourth, the participants were restricted for lifting with their legs. This was done to limit the movement degrees of freedom to the spine and upper extremities. Clearly, the ability to increase the use of lower extremities in lifting could significantly alter the results found in this study.

4.5 Conclusion

With a repetitive asymmetric lifting activity, behavioral changes that increase the risk of back injury included more forward bending, larger twisting moments, and larger three- dimensional movement velocities. This risk was further elevated when lifting activity was preceded by WBV exposure as there was more spine twisting and larger twisting velocities observed with exposure to WBV.

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Chapter 5: Effects of Task Precision Demands on Behavioral and Physiological Changes

during a Repetitive Asymmetric Lifting Activity

5.1 Introduction

Physical factors associated with the development of low back pain (LBP) have been well studied over the past three decades (Frymoyer et al., 1980; Chaffin, 1987;

Bernard, 1997; Marras et al., 1993; Marras et al., 1995; Hoogendoorn et al., 2002; Lotters et al., 2003; Macfarlane et al. 1997; Andersen et al., 2007; Mikkonen et al., 2012;

Lavender et al., 2012; Vandergrift, et al., 2012). Among these, manual work especially repetitive manual lifting has been documented to be associated with development of LBP

(Marras et al., 1993; Hoogendoorn et al., 2002; Lotters et al., 2003; Andersen et al., 2009;

Heneweer et al., 2011; Lavender et al., 2012) and muscle fatigue (Dempsey, 1998).

However, the link between muscle fatigue and low back disorder (LBD) risk is not well understood.

The musculoskeletal system of the human body is adaptive in nature as the body fatigues. In theory, momentary muscle substitution patterns due to development of muscle fatigue result in more variable and less coordinated movements, while still maintaining the same overall behavioral strategy (NRC, 2001). For example, in order to compensate for the loss in strength due to back muscle fatigue, co-contraction of the antagonist muscles may occur to provide stability (Potvin and O’Brien 1998), therein

114 increasing loads on the secondary muscles. Additionally, the development of muscle fatigue due to repetitive manual work would bring about altered behavioral strategies in order to minimize fatigue development (NRC, 2001). Most of the current research on muscle fatigue has looked at biomechanical adaptations associated with repetitive symmetric lifting tasks. These adaptations have been reported as changes in stoop versus squat lifting technique (Trafimow et al., 1993; Bonato et al. 2003) as well as alternating between trunk and hip kinematics (Sparto et al., 1997a; Marras and Granata, 1997).

During an asymmetric repetitive lifting task, Mehta and colleagues (2014) showed these behavioral adaptations to increase in the amount of peak spine flexion, trunk extension and lateral bending velocities, factors identified by the lumbar motion monitor (LMM) model to increase LBD risk (Marras et al., 1993).

Manual lifting tasks may require different degrees of precision during their execution (Drury, 1985). According to Fitts’ Law, an increase in precision demands should also increase the movement time needed to complete the tasks (Fitts, 1954).

Larger movement times with higher precision demands during the lifting task have been reported (Beach et al., 2006; Stambolian et al., 2011). This increase in movement time is largely contributed by a larger deceleration phase (from peak velocity to task completion) in completing the movements (Bootsma et al., 2004). The slower movements during precise work closely approximates a static load (Drury, 1985, Laursen et al., 1988).

Greater co-contraction of the musculature is used to achieve joint stability while performing precise work (Davis et al., 2002). This sustained co-contraction of the

115 muscles during precise work is hypothesized to increase the rate of fatigue development in the affected agonist and the antagonist muscles.

Previously, studies have identified lifting task precision demands to have a significant impact on spinal loading (Davis et al., 2002; Davis and Marras, 2003; Beach et al., 2006). Moreover, repetitive symmetric lifting task with higher precision demands have been reported to increase compressive and shear loads on the spine (Beach et al.,

2006). However, the effect of task precision demands during a repetitive asymmetric lifting on LBD risk has not been investigated. The higher task precision demands during a repetitive asymmetric lifting tasks is also thought to increase the rate of muscle fatigue development and therein, by the yet to be determined mechanism, increase LBD risk.

Thus, the aim of the current study was to understand the behavioral and physiological changes associated with different levels of task precision demands during a repetitive asymmetric lifting activity that is similar to what is often encountered in an occupational setting (Marras et al., 1993; Lavender et al., 2012). Specifically, repetitive asymmetric lifting task under high task precision demands, relative to low task precision demands, is hypothesized to (1) further decrease tissue oxygenation in the back muscles;

(2) decrease motor performance while performing controlled spine flexion-extension motions; (3) increase overall lift duration (4) result in more compensatory behaviors as evidenced by increases in spine kinematic measures; and (5) increase biomechanical loading of the spine.

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5.2 Methods

Experimental Design

This research is part of a larger study investigating the effects of vibration exposure and lifting task precision demands on biomechanical changes experienced during a repetitive lifting task. Since our initial analyses indicated that there were no significant interactions between the lifting demands and the vibration exposure conditions, this paper is focused on analyzing the effects of the task precision demands under the non-vibration condition. The repeated measures design counterbalanced the sequences of task precision conditions across participants and was scheduled at least a week apart. For each of the experimental conditions, participants lifted a box (15% of their maximum capacity) repetitively over a 60 minute period using a stoop posture.

Prior to lifting, participants were seated for 60 minutes.

The dependent variables were selected to assess changes in the physiological and behavioral responses. Changes in muscle physiology were assessed using hemoglobin levels derived from the Near Infrared Spectroscopy (NIRS) signals. Subjective workload during the repetitive lifting task was evaluated using a self report measure (Borg CR-10 scale). Behavioral and biomechanical changes during the repetitive lifting task were assessed using measures of lift duration, hand trajectory, three-dimensional spine kinematics between (T1 and S1) and three-dimensional spine moments. In addition, three-dimensional peak motions were evaluated during a flexion-extension motion assessment protocol (FEMAP) to evaluate changes in motor performance in between the repetitive lifting tasks.

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Sample

Seventeen healthy volunteers, thirteen males and four females between the ages of

18 and 32 (mean = 21.3 years, s.d. = 4.1 years) participated in the study. Mean height and weight of the participants were 1.76 m (s.d. = 0.07 m) and 79.7 kg (s.d. =11.2 kg).

Apparatus

A passive structure was constructed from CreformTM materials to create a circular conveyor system. Lifts originated from a height of 0.25 m above floor, 0.43 m in front of the participants and terminated 0.86 m above floor level, 0.43 m to the participant’s left side. The origin and destination conveyors provided 90 degrees of asymmetry to the participants left side (Figure 26). The destination conveyor had adjustable guide rails that were used to adjust the task precision requirements during box placement. For the low demand condition, there was 0.1m side to side space between the box and the guide rails; conversely, for the high task demands this space was narrowed to 0.006m. The vertical clearance for both task demands remained the same (0.02m). The conveyor frames were fitted on top of Inscale force scales to capture the lift initiation and termination times. The

118 box lifted by the participants was wooden box (0.4 x 0.3 x 0.25m), with handles, and was filled with reams of paper to the desired weight.

Figure 26: Experimental setup used during the lifting task. The subjects lifted the box from the inclined conveyor in front of the body and placed the box on the inclined conveyor positioned on their left side (typical hand trajectory shown as dark black line). The width of the opening on the destination conveyor was adjusted to control the task precision demands (dotted gray – high precision, solid gray – low precision).

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Self report measures (Borg CR-10 scale, Borg, 1982) were obtained to quantify change in the overall subjective workload with repetitive asymmetric lifting. Near-

Infrared Spectroscopy (NIRS) was used to evaluate changes in muscle physiology. The

NIRS system provides a direct measurement of oxygen delivered and utilized at the muscle site. A two-channel INVOS 4100 Cerebral Oximeter (Somanetics Corporation,

Troy, MI, USA) was attached on the back muscles (erector spinae m. at L3 level).

Changes in total, oxygenated and deoxygenated hemoglobin levels were continuously monitored at 85 Hz. Previously, studies have demonstrated oxygenated hemoglobin levels to be more sensitive in detecting physiological changes repetitive work (Ferguson et al. 2013, Mehta et al.2014), thus, this measure has been described further in the paper.

L5/S1. Two Inscale (Terra Haute Indiana) force scales were used to identify the timing of the initial lift and the box placement in the collected data stream during the lifting trials. In addition, left hand sensor data were used to track the box’s trajectory during the lifting activity. Maximum lifting strength, used to scale the box weight for each individual participant’s capability, was measured using a dynamometer.

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Procedures

Eleven motion capture system sensors were attached to the participants: on top the head, at the top of the thoracic spine (T1), over the top of the sacrum (S1), and bilaterally on the upper and lower arms and legs. Additionally, two NIRS sensors were placed bilaterally on the erector spinae muscles at the L3 level.

Each participant’s lifting strength was assessed using a maximum isometric assessment in which the participant attempted to pull upwards on a handle located at the same height and distance from the ankles as the handles on the box during initial part of the lifting task. The strength data were used to adjust the box weight which was adjusted to 15% of maximum lifting strength (indicated by the larger of the two exertions). On average, the box weighed 11.06 kg (s.d. = 3.53 kg).

Next, maximum range of motion (ROM) in the sagittal plane was evaluated.

With eyes closed, participants were asked to bend forward maximally to obtain each individual’s maximum trunk flexion capacity.

Seating task

Prior to lifting, participants were seated upright for 60 minutes without back support so that they started the lifting task after a similar period of inactivity. While seated, participants interacted with a driving simulator to occupy their time. To minimize mental stress during the seating task, participants were instructed that they were not judged on their driving ability. After sitting for 60 minutes, participants performed the flexion-extension motion assessment protocol (FEMAP).

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The Lifting Task

The participants were asked to repetitively lift a box from a conveyor in front of them

(0.25m above the floor) using the handles to the conveyor located to their left side (0.86m above floor) without moving their feet and incorporating a stoop posture. Depending on the session for that day, the guide rails on the destination conveyor were adjusted to the high or low task demand position. The task was paced so that the participants performed 10 lifts/minute for 10 minutes. An audio signal, provided every six seconds, indicated when each lift should be initiated. At the end of each 10-minute lifting period, the Flexion-

Extension Motion Assessment Protocol (FEMAP) which is described below was performed and a Borg scale rating was obtained, after which another 10-minute set of lifting was initiated. This process of lifting for 10 minutes, followed by FEMAP continued until 60 minutes of lifting was completed or until the participant indicated they were fatigued and were no longer able to continue. Where participants terminated their lifting before the end of the 60-minute period, a final FEMAP was performed and a Borg rating was obtained.

Participants were given an opportunity to practice the lifting task before starting the first 10- minute block of lifts.

Flexion-Extension Motion Assessment Protocol (FEMAP)

A procedure was developed to evaluate trunk kinematic performance at the end of the seating task and in between each 10-minutes of the lifting activity (Mehta et al.,

2014). In this procedure the participant, with eyes closed, repeatedly flexed forward to a target position that was defined as two-thirds of their maximum trunk flexion capacity as

122 fast as they could and returned back to an upright standing posture. These motions were repeated 10 times during which spine kinematic data were collected. Spine position information was provided via auditory feedback in that an auditory tone occurred when participants reached the target position and when they returned back to their upright standing posture. During this protocol, participants were allowed to practice the flexion- extension task till they felt comfortable with this procedure.

Data Analysis

Self report scores obtained from Borg scale ratings were used to identify changes in the overall subjective workload during the 60 minutes of the repetitive lifting activity. For the muscle physiology measures, the average of the each 10 minute of the lifting activity was calculated. These data were normalized to the initial 10 minutes of the lifting activity. To assess behavioral and biomechanical changes during the prolonged lifting task, the peak three dimensional spine kinematics and moments along with left hand trajectory were obtained for each lift. The timing of the individual lifts was calculated based on the force scale data.

Means of the duration data, peak kinematic and moment measures for each 10 minutes of lifting activity were computed to identify parameters indicative of behavioral and biomechanical adaptations during lifting. Participants lifted the box using handles; thus, area under the curve for the left hand data was calculated to quantify changes in box trajectories.

While picking was symmetric, box placement was asymmetric relative to the mid-sagittal plane.. Thus, the placement time was calculated as the time taken between the peak extension velocity and the end of the lift (Marteniuk et al., 1987; Castiello et al., 1993). Since twisting

123 motions and lateral bending moment of the spine peaked during box placement; area under the curve for the last 10% of the lift was calculated to identify biomechanical changes associated with task precision demands. For each flexion-extension movement task during the FEMAP, three-dimensional peak motions and movement velocities were obtained.

The resulting data from the NIRS and motion monitor system measures were analyzed using a within subjects repeated measures ANOVA procedure using IBM SPSS

(version 19). For the participants that were not able to complete the 60 minutes of the repetitive lifting task (N = 3, one session each), we used a conservative imputation approach of carrying their last measured value forward so they could be included in the

ANOVA procedures. A paired t-test comparison was conducted when significant interactions were obtained between task precision demands and time. In all statistical tests, a p-value<0.05 was considered to be statistically significant.

5.3 Results

Overall subjective workload

During the lifting task, the overall subjective rating of perceived exertion increased significantly over time (p <0.001). Borg ratings increased by an average rating of 0.4 for every 10 minutes of the repetitive asymmetric lifting activity. However, task precision demands showed no main effect or interaction with time for this variable (p >

0.05).

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Muscle Physiology Measures

For both task demands, the oxygenated hemoglobin levels obtained from the

NIRS system showed significantly high correlations between the left and right erector spinae muscles during the lifting task (> 0.95). Thus, the further description of this measure only includes the right erector spinae muscle physiology measure considering the asymmetry in the lifting task. Figure 27 shows normalized percent change in the levels of oxygenated hemoglobin for the right erector spinae muscle. Overall, oxygenated hemoglobin levels decreased significantly over time during the lifting task

(p<0.001). Task demands showed no main effect or interaction on the muscle physiology measures obtained during the lifting task.

-5 0 10 20 30 40 50 60

change change -10 -15 -20 -25

-30 in oxygenated oxygenated hemoglobin in Normalized percent percent Normalized -35 Time (minutes)

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Behavioral changes with repetitive lifting

Spine kinematic and moment measures that showed significant effects over time during the repetitive asymmetric lifting task are shown in Figure 28. Figure 28a shows the changes in the amount of peak spine flexion over time (p = 0.007). Further, a significant linear trend for this measure shows an average increase of 0.6 degrees for every 10 minutes of the repetitive lifting activity. Twisting and lateral bending motions of the spine showed no significant effect over time. Three-dimensional spine motions were unaffected by task demands or interaction between demands and the prolonged lifting task (p>0.05).

Figure 28b shows changes in the lateral bending moment of the spine. The lateral bending moment of the spine decreased significantly over time (p <0.001). However, task demands showed no effect on this measure. Forward bending and twisting moments of the spine were unaffected by the repetitive lifting activity and task precision demands.

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Figure 28: Changes in the amount of spine flexion (a), lateral bending moment (b) and the three dimensional movement velocities (c) during the repetitive lifting task. Conditions connected by horizontal lines were not statistically different. Error bars represent standard error of the mean.

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Three-dimensional movement velocities of the spine are shown in Figure 28c.

Spine movement velocities increased significantly over time during the repetitive lifting task (p<0.01). A significant linear trend suggests that the extension, twisting and lateral bending velocities of the spine increased by an average of 1.1 degrees/sec, 1 degree/sec and 0.5 degree/sec respectively for every 10 minutes of the repetitive lifting activity.

Additionally, a significant interaction (p = 0.046) between task demands and time for twisting velocity suggests that the overall increase in twisting velocity was mediated by a significant increase in this variable during low task precision demands.

Figure 29a shows the overall lift duration as a function of task demands for the repetitive lifting activity. Overall, the lift duration decreased significantly over time (p <

0.001), with lifting under high task demands taking 6% longer than lifting with low task demands (p = 0.009). Placement times evaluated by calculating the duration between peak extension velocity and the end of the lifting task are shown in Figure 29b. Overall, the placement times decreased significantly over time (p = 0.001). However, a marginal interaction (p = 0.059) suggests that the overall decrease in the placement times was largely contributed by a significant decrease during the low demand tasks (p<0.001).

Additionally, placement times during high demand tasks were 19.8% greater than the low task demands (p = 0.001).

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Figure 30a shows changes in area under the curve calculated for spine twisting motions during the last 10% of the lift. On average, area under the curve for twisting position over time during high task demands were 12% greater as compared to low task

129 demands (p = 0.009). A significant interaction between task demands and time (p =

0.032) was also observed for this variable. The area under the curve for the lateral bending spine moment during the last 10% of the lift is show in figure 30b. On average, area under the curve for the lateral bending moment was significantly greater (10%) during high task demands as compared to the low task demands (p = 0.032) and this was relatively consistent over time

Figure 30: The area under the curve during the last 10% of the lifting task (box placement) for twisting motions (a) and lateral bending moment of the spine (b). Error bars represent standard error of the mean. The “*” indicates where there were statistically significant differences between low and high task precision demands.

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The top view for the left hand trajectory data (final 30 lifts) from a representative subject is shown in figure 31a. Hand trajectory data was quantified by plotting the positions in the sagittal and axial planes for each lift, and calculating the area under the curve. The changes in the area under the curve for this measure are shown in figure 31b.

The overall area under the curve for low task demands was 8.8% larger than high task demands (p = 0.022). Further, a marginal interaction (p = 0.064) between task demands and time indicates that the area under the curve decreased for the lifting activity that required high precision, whereas no change was observed for the low task demands.

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FEMAP

During the FEMAP, spine motions that showed significant effect over time are shown in Figure 32a. The amount of forward spine flexion increased significantly over time (p < 0.001). Whereas, amount of lateral spine flexion showed a marginal effect over time (p = 0.05). The overall change in the amount of lateral spine flexion was between

6.6 degrees and 8 degrees. Twisting motions showed no effect during the FEMAP. The changes in three dimensional movement velocities of the spine during the FEMAP are shown in Figure 32b and 32c. Overall, three-dimensional movement velocities of the spine increased significantly over time (p< 0.05). However, none of the movement velocities sample during the FEMAP showed significant task demand or task-demand by time interaction effects.

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The purpose of this study was to understand the changes in physiological and behavioral responses to 60 minutes of repetitive asymmetric lifting activity under high and low task precision demands. Overall, the perceived physical effort and tissue oxygenation levels during the repetitive lifting activity were unaffected by task precision demands. Behavioral changes with task precision demands resulted in longer lift durations, specifically during box placement phase. Higher task precision demands during the repetitive lifting activity also resulted in larger spine twisting motions and lateral bending moment, especially during the last 10% of the lifts.

Changes in the overall subjective workload

The Borg rating of perceived exertion increased significantly over time during 60 minutes of the repetitive asymmetric lifting activity. These results are similar to prior studies in the literature that have used repetitive lifting task protocol and have shown increase in the level of perceived physical effort over time (Garg and Banaag, 1988;

Bonato et al., 2003; Lotz, Agnew, Godwin and Stevenson, 2009, Mehta et al., 2014).

Additionally, the increase in subjective rating of perceived exertion reported here has been previously demonstrated to increase with development of muscle fatigue (Dedering et al., 1999; Kimura et al., 2007; Hummel et al., 2005; Looze et al., 2009).

In our study, task precision demands showed no effect on the Borg ratings, indicating that the participants did not perceive the high precision task to require more physical effort. One explanation for the null effect is that the development of muscle fatigue associated with the repetitive lifting component of the task could have masked the

135 effects of task precision demands when placing the box at the completion of the lift

(Zadry et al., 2011).

Changes in muscle physiology measure

Oxygenated hemoglobin levels obtained from the erector spinae muscles decreased significantly over time. A decrease in this measure implies reduction in oxygen supply to the muscle site, thereby indicating occlusion of blood flow which may lead to muscle fatigue (Moritani et al., 1992; Perry et al., 2010). Even though we did not measure blood flow, there is evidence that supports development of muscle fatigue measured via changes in the tissue oxygenation levels. This is supported by studies showing that the development of muscle fatigue, as measured with EMG spectral analysis, is associated with a decrease in oxygenated hemoglobin levels (Miura et al.,

2000; Yamada et al., 2008; Ferguson et al., 2013). Thus, the decreased oxygenated hemoglobin levels reported in the current study indicates the development of erector spinae muscle fatigue during the repetitive asymmetric lifting activity (Mehta et al.

2014).

Our hypothesis that lifting under high task demands leads to larger decline in tissue oxygenation levels was not supported. The similar declines in the levels of erector spinae oxygenation levels for high and low task precision demands suggest the initial portion of lift, which was performed in a stooped posture, more heavily affected this measure. We had expected that the increased joint stability requirement when performing the high precision tasks would have led to increased co-contraction of the

136 abdominal muscles and therefore increased activation of the agonistic erector spinae muscles (Laursen et al., 1998; Davis et al., 2002) and therefore, increased the rate of fatigue in the erector spinae muscles. In our study, we did not collect physiological data from the abdominal muscles. This measure would have indicated if abdominal muscle activation was sensitive to the task precision demands.

Behavioral changes associated with task precision demands

Our hypothesis that high task precision demands leads to behavioral and biomechanical changes during the repetitive asymmetric lifting activity was supported.

The overall lift duration was significantly greater when lifting under high task precision demands. These results are in agreement with prior lifting studies that have also shown larger movement times for higher task precision demands (Beach et al., 2006; Stambolian et al., 2011). The overall increase in movement time with precision demands is in accordance with Fitts’ Law (Fitts, 1954). In our study, the task design resulted in a net index difficulty of 4.06 between high and low task precision demands (calculated as log2 of the ratio between low and high task precision demands width); this should have resulted in larger differences in movement time as opposed to the relatively small magnitude of 6% seen in this study. One potential reason for the relatively small effect is that the vertical clearance on the destination conveyor could pose as a larger constraint when placing the box under the low precision demand condition. However, participants were instructed to place the box on the destination conveyor and the vertical bars were offset to the back on the destination conveyor. Another possible reason for the relatively

137 small effect is that participants might have not used the entire width on the conveyor during the low precision demands task. To examine this, variability (standard deviations) in the horizontal hand location during box placement was calculated. The data revealed that variability in the horizontal hand position during box placement under low precision demands was 1.6 times greater than high task precision demands (SD for box placement during low and high task precision demands were 0.036 and 0.022 respectively). Thus, the effective index of difficulty between low and high task precision demands was 0.67

(calculated as log2 of the standard deviation ratio). It is possible that the design of the apparatus constrained the movement variability. For example, the location of the rollers on the destination conveyor could have resulted in smaller effective target width despite the larger width available on the destination conveyor under low precision task. Hence, the constraint that the box be placed adequately on the two rollers comprising the destination conveyor would have led to less of the task precision demands than originally thought and therefore smaller differences in the overall movement times.

While the difference in the overall movement times between the high and low precision placement tasks were of relatively small magnitude, a closer look at the data revealed that under high precision demands participants took significantly longer time

(19.8%) to place the box (Figure 29b). This was primarily due to a shortening of placement times in the low precision demand condition after the first 10 minutes of lifting. Others have found placement time (deceleration phase) differences during precise arm movements (Marteniuk et al. 1987; MacKenzie et al. 1987; Castiello et al. 1993). It can be speculated that the larger placement times allowed participants to correct for any

138 errors while placing the box. Further, in order to achieve better control while placing the box, participants opted for a strategy wherein the box was brought closer to the body and then moved laterally towards the conveyor at the completion of the lift (Figure 31a), which yielded a smaller area under the curve for the hand trajectory data (Figure 31b) and larger lateral bending moments during box placement. The shorter box placement times in the low precision condition suggest the use of more ballistic movement strategies.

In this study, spine twisting and lateral bending moments peaked during box placement. When these measures were analyzed during the last 10% of the lift, the overall twisting motions towards the end of the lifts were 12% larger for high task precision demands. A significant interaction for spine twisting motions suggest that under high task precision demands, the overall twisting motions did not change over time; whereas for the low task precision demands, participants reduced their twisting motions over time. The larger precision requirements during placing for high task demands would have forced the participants to twist their spine for accurate box placements. It is known that larger sustained twisting motions during high demand tasks can cause axial creep of the spine (Shan et al. 2013), thereby, increasing the risk of injury to the passive stabilizing structures of the spine. Twisting motions have also been reported to increase coactivity from the trunk musculature (Lavender et al, 1993; Marras and Granata, 1995), and increased co-contraction has been demonstrated to increase LBD risk (Granta and Marras, 1995).

During the last 10% of the lift, lateral bending moments of the spine were also significantly greater for high task demands, suggesting a static posture during placement.

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Even though the overall moment decreased over time, there is evidence to suggest that a higher sustained lateral bending moment would increase LBD risk (Marras et al., 1993).

Behavior changes associated with time

Behavioral changes associated with the repetitive asymmetric lifting task were observed as an increase in the amount of peak spine flexion and three dimensional movement velocities. Lateral bending moment of the spine and the overall lift duration decreased with the repetitive lifting tasks. These results are similar to our prior work that reported changes in spine kinematic and moment measures with the repetitive lifting activity (Mehta et al. 2014). Larger forward bending motions have been demonstrated to increase the viscoelastic creep of the passive tissues (Adams and Dolan, 1996; Parkinson et al., 2004); whereas an increase in three-dimensional movement velocities have been reported to increase dynamic spine loading and trunk muscle co-activation (Marras and

Mirka, 1993; Dolan and Adams, 1993), thereby increasing the risk of back injury

(Granata and Marras, 2000; Granata and England, 2006). Additionally, three of the five measures that increased over time (forward flexion, twisting and lateral bending velocities) have also been shown to be low back injury risk factors in the lumbar motion monitor risk model (Marras et al., 1993).

FEMAP

The flexion-extension motion assessment protocol was developed to test whether prolonged repetitive asymmetric lifting under task precision demands leads to

140 deterioration in motor performance when performing simple flexion-extension task. Our hypothesis was partially supported in that participants showed an increase in peak spine flexion across the seven FEMAPs which were conducted every 10 minutes. Larger spine flexion motions during the FEMAP are in accordance with the lifting data suggesting creep in the passive structures of the spine (Adams and Dolan, 1996). However, similar time varying changes in the FEMAP under low and high task demands suggests a larger role of the prolonged repetitive stoop lifts in development of viscoelastic creep than any contribution of the task precision demands.

There were some limitations that should be acknowledged concerning this study.

Second, the workplace layout was fixed in our study. Due to this, the relative work height and reach distance to the box would have varied with the anthropometric diversity in the sample. Third, the participants were restricted from lifting with their legs. This was done to limit the movement degrees of freedom to the spine and upper extremities.

Clearly, the ability to increase the use of lower extremities in lifting could significantly alter the results found in this study especially when lifting under high task demands.

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5.5 Conclusions

This study shows that the risk of back injury during asymmetric repetitive lifting is further elevated when the repetitive lifting activity required precise placement of the object at its destination. Specifically, the sustained physical effort required in performing the precise placement task increased the overall lift duration, spine twisting motions and lateral bending moments, all factors that have been associated with an increased risk of back injury (Marras et al., 1993 and 2010).

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Chapter 6: Movement Variability during Repetitive Asymmetric Lifting Task

6.1 Introduction

The previous chapters demonstrated that the overall changes in spine kinematic and moment measures during a repetitive asymmetric lifting tasks are likely to increase the risk of back injury. In addition to the overall magnitude, variability in the movement behavior is another factor that may explain the nature of back injury risk while performing repetitive manual work. Variability in movement behavior may also be a compensatory strategy to prolong the process of fatigue development in order to preserve the overall task performance.

An increase in variability of the muscular response and movement behavior can prolong the muscle fatigue development process. In their study, van Dieen et al. (1993) showed larger variability in the EMG signals for participants that showed longer endurance time (an indicator of fatigue). The authors attributed the delay in the development of fatigue to this increased variability. Similar variations in muscle use during a fatiguing shoulder task have also been demonstrated (Falla and Farina, 2007;

Farina et al., 2008). In addition to increased variability in the muscular response, studies have also reported an increase in cycle-to-cycle variability in the kinematic measures obtained during repetitive fatiguing work. During a repetitive reaching task, Fuller and colleagues (2011) showed larger variability of the elbow and shoulder joints with the

143 development of shoulder muscle fatigue. Similarly, an increase in movement variability has been reported during repetitive sawing activity (Gates and Dingwell, 2011).

Collectively this suggests movement variability during repetitive work to be a compensatory mechanism that permits one to generate the forces necessary to complete a task when the primary muscles start to fatigue.

Larger movement variability may also impose greater loads on the underlying structures. Specific to the low back region, the risk to injury increases if variations in the movement behavior create biomechanical loads that exceed tissue tolerance limits (Mirka and Marras, 1993). For a constrained repetitive lifting task, van Dieen et al. (2001) showed peak (95th percentile) compressive loads to be 20% greater than median compressive loads, thereby demonstrating larger within subject variability with the development of muscle fatigue. During repetitive lifting exertions, Granata et al. (1999) showed trial-to-trial variability accounted for 14% and 32% of the total variation in spine compressive and shear forces respectively. The increase in movement variability with the development of muscle fatigue indicates modulation of motor control that can increase peak loading (Kelaher, 2006).

The goal of this chapter was to explore and understand the variability in the movement behavior while performing a repetitive asymmetric lifting activity and during the flexion-extension motion assessment protocol (FEMAP) performed in between blocks of the lifting activity. Additionally, the chapter explores the aberrations in movement behavior that may increase the risk to back injury especially when lifting activity is

144 preceded by exposure to whole body vibration, and when lifting under high and low task precision demands.

6.2 Methods

Spine kinematic and moment data obtained from study 2 (Chapter 3) were used in the analyses. Similar to Chapter 4 and 5, the lifting and the FEMAP data were separately analyzed for vibration exposure and task precision demands.

Standard deviations and 95th percentile values were calculated to assess variability and peak loading, respectively, during the repetitive asymmetric lifting task and while performing controlled flexion-extension spine motions.

Standard Deviation Approach

The purpose of this approach was to understand variability in the spine kinematic and moment measures. During the repetitive lifting activity, standard deviation values from the mean were computed for each 10-minute lifting block. For the FEMAP, standard deviations were calculated for the 8 flexion-extension motions performed after every 10 minutes of the repetitive lifting activity. A repeated measures ANOVA procedure was conducted to identify significant main effect and interactions for each dependent variable (p < 0.05).

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95th percentile Approach

While the previous approach allows understanding of the variability in the behavioral and biomechanical measures, this approach quantified aberrant behaviors that may increase peak loads acting on the spine. For every 10 minutes of the repetitive lifting block and flexion-extension motion during the FEMAP, the 95th percentile values were calculated for each dependent measure and for each condition. A repeated measures ANOVA procedure was used to identify significant main effect and interaction

(p < 0.05).

6.3 Results

Vibration Exposure

Repetitive lifting activity

Standard Deviation (SD) Approach

Exposure to WBV resulted in significantly larger standard deviations (7.9) for the lateral bending moment (LBM) on the spine as compared to lifting activity that was preceded by quiet sitting (7.0).

Overall, the variability in three-dimensional movement velocities of the spine increased significantly over time (Table 6). Whereas, the variability in the overall lift duration decreased significantly over time.

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Table 6: p-values using the SD approach for the Lifting Data (vibration effect).

Forward Lateral Lateral Forward Lateral Bending Twisting Bending Extension Twisting Bending Bend Twisting Bend Moment Moment Moment Velocity Velocity Velocity Duration Vibration (V) 0.414 0.692 0.088 0.226 0.564 0.037 0.445 0.633 0.400 0.740 Time (T) 0.473 0.073 0.521 0.561 0.362 0.191 0.050 0.042 0.004 <0.001 V x T 0.063 0.996 0.325 0.418 0.789 0.233 0.045 0.502 0.436 0.841

A significant interaction between vibration exposure and time for extension velocity (Figure 33) suggests that the variability in this measure increases over time when participants were exposed to WBV (p = 0.004), whereas no effect was observed when the lifting activity followed quiet sitting (p = 0.397).

10 8 6 Vibration 4

StandardDeviation 2 No-Vibration 0 10 20 30 40 50 60 Time (minutes)

Figure 33: Changes in the SD values for extension velocity of the spine as function of vibration exposure during the repetitive asymmetric lifting activity.

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95th percentile Approach

Table 7 shows the overall p-values obtained from the ANOVA procedure using the 95th percentile approach for the repetitive lifting task. During the repetitive lifting task, the 95th percentile values for spine flexion, twisting moment, and the three- dimensional movement velocities increased significantly over time. Additionally, the

95th percentile values for the lateral bending moment and the lift duration decreased significantly over time.

Table 7: p-values for the 95th percentile values during the repetitive lifting task.

Forward Lateral Lateral Forward Lateral Bending Twisting Bending Extension Twisting Bending Bend Twisting Bend Moment Moment Moment Velocity Velocity Velocity Duration Vibration (V) 0.671 0.251 0.748 0.053 0.785 0.84 0.623 0.040 0.426 0.622 Time (T) 0.041 0.410 0.380 0.090 0.008 <0.001 0.020 <0.001 <0.001 <0.001 V x T 0.979 0.258 0.992 0.375 0.154 0.725 0.114 0.797 0.749 0.186

The 95th percentile value for spine twisting velocity was significantly greater when participants were exposed to WBV (77.26 degrees/sec) as compared to lifting preceded by quiet sitting (71.74 degrees/sec).

FEMAP

Standard Deviation (SD) Approach

Table 8 shows the p-values from repeated measures ANOVA for spine kinematic measures during the FEMAP. The repetitive lifting activity only affected the variability in the extension velocity of the spine measured during the FEMAP. When WBV

148 preceded the lifting task, significantly larger standard deviations (17.4) were observed as compared to quiet sitting (15).

Table 8: p-values using the SD approach for the FEMAP.

Forward Lateral Forward Lateral bending Extension Twisting bending Bend Twisting Bend velocity velocity velocity velocity Vibration (V) 0.121 0.536 0.649 0.495 0.027 0.097 0.373 Time (T) 0.029 0.195 0.170 0.611 0.504 0.644 0.074 V x T 0.702 0.624 0.741 0.731 0.341 0.039 0.363

Further, a significant interaction for the twisting velocity suggests exposure to

WBV increases the variability in this measure, while no change was observed when lifting activity followed quiet sitting. A t-test comparison showed the variability in this measure to be significantly higher when exposed to WBV but only after 60 minutes of repetitive lifting (Figure 34).

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10 9 * 8 7 6 5 4 3 Vibration 2 StandardDeviations No-vibration 1 0 10 20 30 40 50 60 Time (minutes) .

Figure 34: Changes in the SD for twisting velocity of the spine as function of vibration exposure during the FEMAP, “*” indicates p < 0.05.

95th percentile Approach

The 95th percentile values for the three-dimensional movement velocities of the spine measured during the FEMAPs increased significantly over time (Table 9). The amount of spine twisting also showed a significant main effect over time. However, the

95th percentile values for spine twisting motions increased for the first three FEMAPs, after which no change was observed for this measure.

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Table 9: p-values for the 95th percentile values during the FEMAP. Forward Lateral Forward Lateral Bending Extension Twisting Bending Bend Twisting Bend Velocity Velocity Velocity Velocity Vibration (V) 0.847 0.442 0.799 0.651 0.752 0.14 0.429 Time (T) 0.170 0.021 0.171 <0.001 0.007 0.043 0.005 V x T 0.882 0.700 0.812 0.5 0.967 0.031 0.22

A significant interaction for spine twisting velocity suggest that the 95th percentile values increased significantly over time when participants were exposed to WBV (p =

0.013), whereas no change in this measure was observed across the six FEMAPs that followed quiet sitting (Figure 35).

50 *

30 Vibration

degrees/sec 20 No-vibration 10

0 10 20 30 40 50 60 Time (minutes)

Figure 35: 95th percentile twisting velocity as a function of vibration exposure during the FEMAP, “*” indicates p < 0.05.

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Task Precision Demands

Repetitive lifting activity

Standard Deviation (SD) Approach

The overall p-values using the SD approach for the lifting data are shown in table

10. Task precision demands showed a significant main effect on the lateral bending motions and lift duration (Table 10). On average, variability in the lateral bending motions was significantly higher when lifting under low precision demands (2.03) as compared to high precision demands (1.76). Contrastingly, the variability in lift duration was significantly higher when lifting activity was performed under high task precision demands (0.21) as compared to low precision demands (0.14). While the overall variability in the lateral bending velocity of the spine increased significantly over time, the variability in lift duration decreased significantly over time (table 10).

Table 10: p-values using the SD approach for the Lifting Data (precision demands effect).

Forward Lateral Lateral Forward Lateral Bending Twisting Bending Extension Twisting Bending Bend Twist Bend Moment Moment Moment Velocity Velocity Velocity Duration Demand (D) 0.576 0.367 0.033 0.160 0.656 0.222 0.487 0.686 0.307 0.002 Time (T) 0.069 0.916 0.953 0.955 0.276 0.827 0.617 0.447 0.044 0.007 D x T 0.153 0.403 0.971 0.668 0.239 0.688 0.467 0.967 0.734 0.303

95th percentile Approach

The 95th percentile values for the spine kinematic, moment and duration measures were unaffected by task precision demands (Table 11). However, the 95th percentile values for twisting moment, twisting and lateral bending velocities of the spine increased

152 significantly over time, and the lateral bending moment along with the lift duration decreased significantly over time.

Table 11: p-values for the 95th percentile values during the repetitive lifting task.

Forward Lateral Lateral Forward Lateral Bending Twisting Bending Extension Twisting Bending Bend Twisting Bend Moment Moment Moment Velocity Velocity Velocity Duration Demand (D) 0.254 0.528 0.392 0.488 0.747 0.178 0.266 0.689 0.852 0.001 Time (T) 0.083 0.821 0.542 0.288 0.041 <0.001 0.294 0.002 0.002 <0.001 D x T 0.525 0.535 0.781 0.881 0.219 0.652 0.215 0.654 0.81 0.392

FEMAP

Standard Deviation (SD) Approach

During the FEMAP, variability in the amount of lateral bending and the lateral bending velocity of the spine increased significantly over time (Table 12).

Table 12: p-values using the SD approach for the FEMAP.

Forward Extension Lateral Forward Lateral bending velocity Twisting bending Bend Twisting Bend velocity velocity velocity Demand (D) 0.825 0.282 0.252 0.108 0.266 0.187 0.812 Time (T) 0.125 0.191 0.017 0.091 0.162 0.246 0.005 D x T 0.194 0.296 0.718 0.820 0.526 0.872 0.849

95th percentile Approach

Overall, the 95th percentile values for the amount of forward bending and twisting increased with successive FEMAPs, as did the forward bending and lateral bending 153 velocities. But while the twisting showed a significant main effect over time, a post hoc analysis showed the increase in this measure to occur during the initial three FEMAPs after which no significant change was observed.

Table 13: p-values for the 95th percentile values during the FEMAP.

Forward Lateral Forward Lateral Bending Extension Twisting Bending Bend Twisting Bend Velocity Velocity Velocity Velocity Demand (D) 0.525 0.128 0.365 0.146 0.497 0.064 0.936 Time (T) 0.035 0.029 0.072 <0.001 0.085 0.127 <0.001 D x T 0.36 0.351 0.818 0.402 0.843 0.993 0.646

6.4 Discussion

Overall, the results support the hypothesis that variability in movement behavior increases over time with more exposure to a repetitive asymmetric lifting task. In addition to an increase in movement variability, the 95th percentile (peak) values for spine kinematic and moment measures also increased with continued repetitive lifting.

Standard Deviation Approach

Repetitive Lifting Activity

The repetitive lifting task involved symmetric picking activity and asymmetric placement activity. Since participants were instructed to not flex their lower extremities while performing the lifting task, changes in movement variability for spine moment and movement velocity measures were expected with repetitive lifting activity. For both the

154 analyses (vibration exposure and task precision demands), the variability in the lateral bending velocity of the spine increased with the repetitive lifting activity. These results support the findings from prior studies in the literature that have reported larger variability in movement velocities during repetitive reaching and lifting tasks (Granata et al., 1999; Fuller et al., 2011). With the development of fatigue during a repetitive lifting task, participants could have been adjusting their movement behavior while searching for an optimal movement strategy that minimizes the load experienced by the musculoskeletal system. Thus, the increased variability in movement velocity may indicate a compensatory mechanism to prolong the development of muscle fatigue during a repetitive asymmetric lifting activity (Fuller et al., 2011). Internally, this could be achieved by load sharing (muscle substitution). Specifically, with the development of muscle fatigue, the cortical drive to the secondary muscles would increase (Reeves et al.,

2008; Sparto et al., 1997b), in addition to the recruitment of the primary muscles. Since the secondary muscles function to stabilize the torso, the recruitment of these muscles in generating the force would increase the variability in the movement behavior.

Looking across the effects of vibration exposure and task precision demands it can be seen that increase in the variability for spine extension and twisting velocities was only observed for the vibration exposure analysis. Further, within the vibration exposure analyses, WBV exposure resulted in larger number of changes in the variability of spine kinematic and moment measures as compared to lifting that followed quiet sitting. Thus, it can be speculated that the variability in movement behavior may be associated with the amount of musculoskeletal load (e.g. fatigue, WBV exposure) experienced by the body.

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FEMAP

Complementing the results obtained from the lifting task, seated driving exposure prior to lifting and lifting under task precision demands showed increase in variability for the lateral bending velocity of the spine over time during the FEMAP. However, the variability in spine motions is in disagreement between the two analyses. While, the variations in forward bending motions increased over time when lifting activity was performed under high precision demands, variability in the lateral bending motions increased when lifting activity was preceded by quiet sitting. This discrepancy between the two analyses indicates different strategies used to compensate for muscle fatigue development. Further, by simply looking at the number of variables that showed significant changes in standard deviations over time between the two analyses, these results support the prior speculation that greater musculoskeletal load may increase the variability in movement behavior.

95th Percentile Approach

Repetitive Lifting Activity

In addition to movement variability, there was also expectation for an increase in the 95th percentile peak values for the spine kinematic and moment measures. This hypothesis was supported in that the 95th percentile values for spine twisting moment, twisting velocity and lateral bending velocity increased with repetitive lifting activity.

However, the 95th percentile values for the forward bending motions and extension velocity of the spine only increased for lifting activity performed under the high precision

156 demands condition (with and without vibration exposure). While the increase in peak forward flexion indicates an increase in the laxity of the spine that can increase loading on the passive structures (Adams and Dolan, 1996), an increase in peak movement velocities of the spine exhibits a ballistic movement strategy that would increase the peak loads acting on the spine (Marras and Mirka, 1993; Dolan and Adams, 1993).

FEMAP

In both the analyses (vibration exposure and task precision demands), the peak movements in the axial plane measured in the FEMAPs increased with continued exposure to the repetitive lifting task. These results are in agreement with Parnianpour et al. (1988) and thereby suggest changes in the motor control strategy with the development of muscle fatigue.

Further, the 95th percentile value for the lateral bending velocity of the spine increased over time. This result, in addition to the variability in this measure, indicates that the variations in movement behavior that may prolong the fatigue development process may also increase peak loading on the spinal structures. Specific to the vibration exposure analysis, the three-dimensional peak movement velocities of the spine increased significantly over the successive FEMAPs; although with exposure to WBV, the peak twisting velocity was only larger during the final FEMAP. These results complement the findings from the lifting data that highlights fatigue shifts movement towards ballistic behavior that can increase the risk of injury.

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6.5 Conclusion

In summary, this investigation has demonstrated that a repetitive asymmetric lifting task increases the variability in the movement behavior. While the increase in movement variability may indicate a compensatory mechanism to prolong the fatigue development process, the increase in peak spine kinematic and moment measures suggest the increase in variability would also increase peak spinal loading. Thus, the increase in variability along with an increase in peak spine kinematic and moment measures after exposure to WBV provides insight to the mechanism by which injury risk is elevated in repetitive lifting.

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Chapter 7: Overall Discussion

The purpose of this dissertation research was to explore and understand behavioral and physiological changes associated with prolonged exposure to a repetitive asymmetric lifting activity, and to identify whether these changes affected the risk to back injury. Additionally, to identify changes in movement behavior and muscle physiology measures when repetitive asymmetric lifting tasks follow exposure to whole body vibrations, and when lifting under low and high levels of task precision demands.

The revised conceptual model for this dissertation research is shown in Figure 36.

The research has demonstrated that repetitive asymmetric repetitive stooped lifting task leads to the development of localized muscle fatigue in the erector spinae muscles which was observed as decrease in oxygenated hemoglobin levels. With the development of muscle fatigue, the musculoskeletal system adapted and brought about changes in the behavioral response, changes identified to increase LBD risk. Changes in the neuromuscular response with repetitive stooped lifting activity resulted in larger motions in the sagittal plane even during the controlled flexion-extension task (FEMAP). Where the repetitive asymmetric lifting task was preceded by WBV exposure, increased motion and movement velocity of the spine in the axial plane was observed. Lastly, high task precision demands imposed during repetitive lifting activity also led to longer placement

159 times and larger sustained twisting motions and lateral bending moment, factors identified to increase LBD risk.

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Figure 36: Conceptual model revisited. Italics indicate inferences from the literature.

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7.1 Interpretation of the Results

Study 1 (Chapter 2): The purpose of this study was to investigate the effects of asymmetric repetitive lifting on measures associated with fatigue in the back muscles.

Hypotheses: Asymmetric repetitive lifting task leads to (a) decline in tissue

oxygenation levels (supported), (b) behavioral adaptations that increase the peak

values in kinematic and biomechanical measures (supported), and (c)

deterioration in performing controlled spine motions (supported).

The regression analysis approach used in this study allowed an understanding of the between-subject variation in muscle physiology and behavioral measures with a prolonged exposure to a repetitive asymmetric lifting activity. Even though this approach assumed a linear relationship over time for each dependent measure, this assumption was considered appropriate since some participants that were not able to complete the 60 minutes of repetitive lifting task, and the ones that showed larger changes in their behavioral and physiological responses tended to be more linear (with high r2 values).

Muscle physiology measures obtained from the NIRS system indicated that the overall physiological response from the erector spinae muscles changed with repetitive asymmetric lifting activity. Specifically, all measures of muscle physiology (oxygenated, total and deoxygenated hemoglobin levels) decreased with repetitive lifting activity performed in a stooped posture. Based on the existing literature that have shown

162 association between tissue oxygenation levels and muscle fatigue development (Yamada et al., 2008; Ferguson et al., 2013), this study demonstrated the development of localized fatigue in the erector spinae muscles with the repetitive asymmetric lifting activity.

Additionally, the overall changes in the oxygenated hemoglobin levels from the erector spinae muscles were greater as compared to the total and deoxygenated hemoglobin levels, suggesting this measure is more sensitive for detecting the changes in muscle physiology (Ferguson et al., 2013).

Subjective perception of workload was evaluated using the Borg scale rating (CR

10). With repetitive asymmetric lifting activity, the overall subjective workload increased significantly over time. While an increase in this measure indicates an increase in the overall physiological workload (Capodaglio, 2001; Coutts et al., 2009), this measure has also been reported to be associated with the development of muscle fatigue

(Kimura et al., 2007; Hummel et al., 2005; Looze et al., 2009). These results in combination with muscle physiology measures indicate the development of muscle fatigue with 60 minutes of repetitive asymmetric lifting activity.

The regression approach for the behavioral and biomechanical data provided insight to the considerable amount of variability in movement strategies between individuals during a repetitive lifting task. Despite individual variations, the overall results suggest a common pattern that indicates prolonged exposure to a repetitive lifting activity increases the peak forward bending motions, extension and lateral bending velocities of the spine; the lateral bending moment of the spine and lift duration decreased over time during the prolonged lifting activity. Further, a significant

163 correlation between behavioral and muscle physiology measures indicate the changes in movement behavior to be associated with the development of erector spinae muscle fatigue.

Spinal stability has been reported to decrease with the development of muscle fatigue (Granata et al., 2004). Thus, changes in the movement behavior seen as an increase in three-dimensional movement velocities of the spine may be a compensatory mechanism to restore spinal stability by increasing joint stiffness and overcoming delay in the neuromuscular response. However, these changes may also be responsible in increasing the risk to injury. Specifically, movement strategy that resulted in larger forward bending motions of the spine would increase loading of the passive structures

(Adams and Dolan, 1996; Parkinson, Beach and Callaghan 2004). Second, larger movement velocities with repetitive lifting activity would increase trunk muscle co- activation (Marras and Mirka, 1993; Dolan and Adams, 1993), which while providing increased stability (Granata and Marras, 2000; Feltham et al., 2006), increases the biomechanical loads on spinal structures (Davis and Marras, 2000; Granata and England,

2006).

While an increase in forward bending motion and movement velocities increase the risk to injury, any decrease in lateral bending moment of the spine may reduce the lateral shear force on the spine (Marras et al., 1999). Even though there was an overall decrease in the lateral bending moment of the spine, the data suggest that the overall injury risk would vary depending on the sub-strategies used in reducing these moments.

To reduce the lateral bending moment of the spine, some participants showed a lateral

164 shift of the sacrum towards the destination conveyor while placing the boxes which reduced the horizontal reach distance and thereby reduced their lateral bending moment

(Lavender et al., 1999), whereas other participants showed larger twisting motions of the spine. The increase in spine twisting motion to reduce the lateral bending moment of the spine would increase co-contraction of the trunk musculature (Marras and Granata, 1995) and resulting spine loads.

The flexion-extension motion assessment protocol was performed to quantify changes in motor performance during a controlled spine bending motion task in the sagittal plane. With continued exposure to repetitive lifting, trunk motor performance decreased over time seen as an increase in sagittal plane range of motion. The increased motion in the sagittal plane suggest development of creep in the passive structures of the spine (Adams and Dolan, 1996) or increased delay in the neuromuscular control that can reduce spine protection towards the end range of motion specifically during sudden loading.

In summary, repetitive asymmetric lifting activity leads to development of muscle fatigue in the erector spinae muscles. Fatigue related changes in movement behavior increase the forward bending motions and movement velocities of the spine. These behavioral changes provide insight to the nature of injury risk associated with repetitive work. In addition to the behavioral changes, a repetitive lifting task also reduces the individual’s ability to perform controlled spine motions in the sagittal plane.

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Study 2: The purpose of this study was to investigate the effects of task precision demands and vibration exposure in combination on muscle physiology, motor performance and lifting mechanics. The specific aims of this study were as follows:

Aim 1: Investigating the effects of seated whole body vibration exposure on measures associated with fatigue in the back muscles during a subsequent repetitive lifting task.

Hypothesis 1: WBV exposure preceding an asymmetric repetitive lifting task

leads to (a) a larger decline in tissue oxygenation levels (not supported), (b)

behavioral adaptations that increase the peak values (supported) and variability

(supported) in kinematic and biomechanical measures, and (c) deterioration in

performing controlled spine motions (partially supported) as compared to a lifting

task that is preceded by sitting without vibration exposure

Aim 2: Investigating the effects of repetitive lifting task’s precision demands on back muscle fatigue measures

Hypothesis 2: Lifting repetitively under high task precision requirements reduces

the variability in lifting behavior (partially supported) and therefore increases the

rate of fatigue in the back muscles measured through tissue oxygenation (not

supported), behavioral adaptations (supported) and changes in motor

performance measures (not supported) relative to a lifting task with low precision

requirements.

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Aim 3: Understanding the interaction between vibration exposure and task precision demands on measures of muscle fatigue during a repetitive asymmetric lifting task.

Hypothesis 3: The combination of WBV and high task precision demands during

lifting results in quicker fatigue development as measured though tissue

oxygenation, behavioral adaptations and changes in motor performance relative

to conditions with only whole body vibration exposure or high task precision

demands (not supported).

My overall hypotheses that exposure to WBV and lifting under high task precision demands brings about behavioral and physiological changes that are either additive or multiplicative as compared to lifting under low precision demands that follows quiet sitting was not supported. Specifically, I found no significant interaction between whole body vibration exposure and task precision demands during the repetitive lifting activity and during the FEMAP on any of the dependent measures (Chapter 3).

Thus, the data for this study was separated into two analyses, where study 2a (chapter 4) looked at the effects of seated vibration exposure on lifting activity (under high precision demands) and study 2b (chapter 5) looked at the effects of lifting task precision demands after quiet seating.

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Effect of Whole body vibration (Study 2a – Chapter 4 and 6)

Results from this study validated my findings from study 1 that showed repetitive asymmetric lifting activity to increase the subjective perception of the overall workload, as well as decrease the physiological response from the erector spinae muscle.

Additionally, the behavioral and motor performance changes observed in this study are in agreement with spine kinematic and moment changes found in study 1.

Despite the overall increase in the subjective ratings of perceived exertion, this measure was unaffected by exposure to WBV during the simulated driving and the lifting task. The null effect found here suggests that the overall subjective workload is largely affected by the prolonged lifting activity independent of whether vibration exposure preceded this activity.

Similarly, no effect of WBV exposure was seen for muscle physiology measures.

The current literature on the effects of WBV exposure on fatigue development is inconclusive (Hansson et al., 1991; Pope et al., 1998; El Falou et al., 2003; Santos et al.,

2008). My results support the findings from prior research that have reported no changes in erector spinae muscle fatigue with exposure to seated WBV (El Falou et al., 2003;

Santos et al., 2008). The null effect highlights the need to understand muscle physiology at secondary and antagonist muscle sites as exposure to WBV may increase co- contraction from their trunk muscles. I speculate that exposure to WBV could have fatigued the abdominal muscles in addition to the fatiguing back extensor muscles. This study did not measure abdominal muscle physiology; perhaps measurement of the

168 abdominal muscle physiology would provide insight to the level of co-activity and fatigability of the abdominal muscles after exposure to WBV.

Behavioral changes seen in this study validated the findings from Study 1, thereby indicating the increased risk to injury during repetitive lifting work may be a result of the changes in lifting mechanics. In addition to these overall changes, participants exposed to WBV showed significantly larger twisting motion and twisting velocity of the spine during the repetitive asymmetric lifting activity. Exposure to WBV has been reported to increase delay in the feedback response of the neuromuscular system (Wilder et al., 1996;

Li et al., 2008; Arora and Grenier, 2013). Thus, the delay in the braking mechanism while placing the box could have resulted in larger twisting motions. Further, the larger twisting velocity observed after exposure to WBV could be a coping strategy to compensate for the poor feedback response in restoring spinal stability while performing repetitive lifting tasks. Individually, larger spine twisting motions have been shown to cause rotational creep of the spine (Shan et al., 2013); rotational creep after exposure to

WBV along with forward bending creep with repetitive lifting increases the risk of injury to the passive stabilizing structures. Twisting velocity is one of the five risk factors used to determine LBD risk with the LMM model (Marras et al., 1993). Both twisting motions and twisting velocity have been reported to increase coactivity from the trunk musculature (Marras and Granata, 1995 and 1997); and increased co-contraction has been demonstrated to increase LBD risk (Granta and Marras, 1995). Thus, the behavioral changes specific to the axial plane associated with repetitive asymmetric lifting activity

169 after exposure to WBV indicates the elevated back injury risk associated when repetitive lifting follows WBV exposure.

During the FEMAP, I expected to see decrements in motor performance with exposure to WBV. However, my results only partially support this hypothesis. Changes in the sagittal plane range of motion increased over time; however, this increase was similar with and without vibration exposure suggesting the development of creep or reduced neuromuscular control. Even though I found an overall increase in three- dimensional movement velocities sampled during the FEMAPs, the data suggest the increases in peak extension velocity (figure 22a) and peak twisting velocity (figure 22b) are affected by exposure to WBV. It is possible that increase co-activation of the trunk musculature during exposure to WBV could have fatigued the abdominal muscles, as speculated earlier, which may have resulted in faster movements to restore stability.

The variability (standard deviations) in three-dimensional movement velocities also increased with the repetitive lifting activity. While an increase in movement variability may suggest compensatory mechanisms to delay the fatigue development process or an effort to find an optimal solution to preserve task performance with fatigue, changes in movement variability along with an increase in 95th percentile peak values indicate aberrant behaviors with repetitive lifting activity. Further, these aberrant behaviors in the axial plane increased when people were exposed to WBV. Specifically, the shift in lifting strategy towards a ballistic behavior may increase peak loads acting on the spine and thereby increase the risk to injury after WBV exposure.

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In summary, this study has validated my findings from study 1 that have shown fatigue related changes in movement behavior to increase the risk to back injury.

Although the results from this study did not indicate an overall increase in erector spinae muscle fatigue via objective and subjective measures with exposure to WBV, larger behavioral changes (mean and 95th percentile) along with greater movement variability suggest WBV exposure to impose greater loads on the musculoskeletal system.

Effect of Task Precision Demands (Study 2b – Chapter 5 and 6)

The data from this study was used to understand changes in physiological and behavioral response to repetitive asymmetric lifting activity under low and high levels of task precision demands.

Similar to the exposure analysis, the overall subjective workload was unaffected by task precision demands during the repetitive lifting activity. These results suggest the larger role of the prolonged stooped lifting on the overall perceived workload experienced by the worker.

My hypothesis that high precision task demands lead to larger decrease in muscle physiology measures was not supported. Changes in oxygenated hemoglobin levels were similar between high and low precision task demands. The similar declines in muscle physiology measures suggest that the initial phase of the stooped lifts heavily affect this measure. I expected that, the increased joint stability requirement when performing the high precision tasks would have led to increased co-contraction of the abdominal muscles and therefore increased activation of the agonistic erector spinae

171 muscles (Laursen et al., 1998; Davis et al., 2002). Thus, the effect of task precision demands on muscle physiology could be present in measurement of abdominal or perhaps shoulder muscle physiology; future studies can investigate the effects of repetitive lifting task demands on abdominal and shoulder muscle physiology.

In addition to the overall behavioral changes, high task precision demands during the repetitive lifting activity resulted in larger behavioral changes as compared to low task precision demands. Specifically, the overall lift duration during high task precision demands was significantly greater than during low precision demands (Beach et al.,

2006; Stambolian et al., 2011); this in accordance with Fitt’s Law (Fitts, 1954). Even though differences in the overall lift duration were of a relatively small magnitude (6%), the differences in movement times were significantly larger when placing the box

(19.8%). The longer placement times in performing the lifting task under high precision demands could increase the risk to back injury as strong association have been identified between lift duration and the risk to back injury by Marras et al. (2010) in their large study of distribution center workers.

In order to achieve better movement control, and correct for movement errors while placing the box, participants on average opted for a strategy wherein the box was brought closer to the body and then moved laterally towards the conveyor at the completion of the lift. This yielded a smaller area under the curve for the hand trajectory data and larger lateral bending moments during box placement. Specifically, during the last 10% of the lift, lateral bending moments of the spine were significantly greater for high task demands, suggesting a static posture during box placement. Even though the

172 overall moment decreased over time, there is evidence to suggest that a higher sustained lateral bending moment would increase LBD risk (Marras et al., 1993).

Additionally, during the last 10% of the lift, the overall twisting motions were

12% larger for high task precision demands. Moreover, a significant interaction for spine twisting motions suggest that under high precision task precision demands, the overall twisting motions did not change over time; whereas for the low task precision demands, participants reduced their twisting motions over time. The larger precision requirements during placing for high task precision demands would have forced the participants to twist their spine for accurate box placements; this can cause axial creep of the spine (Shan et al., 2013), thereby, increasing the risk of injury to the passive stabilizing structures of the spine. Further, twisting motions would also result in larger trunk muscle coactivity (Lavender et al., 1993; Marras and Granata, 1995) and increase

LBD risk (Granta and Marras, 1995).

Task precision demands showed no effect on spine kinematic and kinetic variables during the FEMAP. Even though there was an overall increase in peak forward bending motions of the spine over time, the similar effect seen under low and high task precision demands suggests a larger role of the prolonged repetitive stoop lifts in development of viscoelastic creep or deterioration of neuromuscular control than any contribution of the task precision demands.

While movement variability in the lateral bending motions of the spine was higher with low lifting demands, the variation in lateral bending velocity of the spine increased over time during the lifting activity and the FEMAP. As mentioned earlier, the larger

173 variation in movements could prolong the development of muscle fatigue; however, the increase in the 95th percentile values for spine kinematic and moment measures during the lifting activity would indicate that this variation increases peak loading on the spine structure. This shift towards ballistic movements may explain the injury risk associated with repetitive lifting activity.

In summary, task precision demands showed no effect on subjective and objective measures of muscle fatigue. However, larger movement variability along with increase in the overall magnitude (mean and 95th percentile) of the spine kinematic and moment response explain the nature of injury risk associated with repetitive lifting activity. The risk to injury is further increased when lifting activity is performed under high levels of task precision. Specifically, movement behaviors during the static component of the repetitive lifting task (under high levels of task precision) increases the amount of spine twisting motion, lateral bending moments and placement times; factors identified to increase the risk of injury.

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7.2 Limitations

Like many controlled laboratory studies, there were several limitations that should be acknowledged concerning this dissertation work. First, all my participants were novice manual handlers from a university population. In this dissertation work, I was looking to understand behavioral adaptations associated with repetitive lifting tasks after exposure to WBV, and lifting under low and high task precision demands. Inexperienced individuals would allow understanding these behavioral changes as they lift repeatedly in a new environment. Experienced manual handlers would have already adopted an optimal strategy to perform the repetitive lifting task. Previous studies have shown differences between experienced and inexperienced lifters (Marras et al., 2006; Lee and

Nussbaum, 2012). Hence, one should be cautious in generalizing the results obtained from this research to experienced lifters.

Second, the workplace layout was fixed in both my studies. This control was enforced to simulate a real work environment where the workplace layout is often fixed within a job. The origin and destination conveyor height was approximately at individual’s ankle and waist level respectively and the participants were standing at a fixed distance from the origin and destination conveyors. Due to this, the relative work height and reach distance to the box would have varied with the anthropometric diversity in the sample. This could have varied the three-dimensional spine moments, and limiting the adaptations that could have been performed.

Third, participants were restricted from lifting with their legs. This control was enforced to limit the degrees of freedom available to the spine and upper extremities.

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Some of the results, especially movement times could have been significantly affected by this control. Clearly, the ability to increase the use of lower extremities in lifting could significantly alter the results found in these studies, especially when lifting under high task precision demands and lifting preceded by exposure to WBV.

Fourth, during the simulated driving (seated) task, the participants were not provided with a backrest. This was deliberate to simulate a worst case scenario during the seating task. Additionally, the presence of a backrest would have hindered the motion monitor and NIRS sensors attached to the lower back. An addition of a backrest would substantially change the transmission of vibrations to the human body (Hinz et al.,

2002), and thus alter the behavioral and physiological measures obtained in study 2

(chapter 4 and 6).

Lastly, the NIRS system was a 2-channel system; this did not allow measurement of abdominal and shoulder muscle activation. It is possible that the null effect seen in study 2 for the muscle physiology measures may have been due to the inability in measuring physiological changes at the abdominal and the shoulder muscles.

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7.3 Future Directions

Behavioral changes seen in this dissertation work provide insight regarding the nature of back injury risk when performing repetitive asymmetric lifting activity. Future studies can use a similar protocol to test if experienced manual lifters use a similar strategy during repetitive lifting work. In addition to these behaviors, Madeleine et al.

(2008) showed experienced workers to illustrate larger movement variability during a repetitive cutting task. Perhaps, the effect seen for movement variability could be evaluated among experienced workers to understand if variability in movement behavior would be a compensatory mechanism with repetitive manual work.

Based on the results, future studies can also look at the behavioral and physiological changes associated with repetitive upper extremity and lower extremity movements. Specifically, to validate the behavioral changes (increased laxity and ballistic movement strategy) and to understand if these changes apply to other regions of the body when performing repeated fatiguing movements.

This research looked at a single frequency and amplitude of vibration during the seated task. Future studies can look at the changes in muscle physiology and lifting mechanics by modulating WBV characteristics, including frequency, amplitude, and the transient mechanical shock components of non-periodic vibrations (jarring and jolting).

Future studies can also look at the changes in muscle physiology measured with

NIRS across several muscle sites on the trunk and the shoulders. These studies would allow in identifying muscle recruitment pattern related to these behavioral adaptations.

Specifically, to understand if secondary or antagonist muscles start to fatigue (or show

177 changes) after certain period of repetitive lifting and if there is switching between muscle groups to allow temporary recovery.

The amount of musculoskeletal load experienced by the body is also hypothesized to increase the number of spine kinematic and moment measures showing changes in movement variability. Future studies can vary the load experienced by the body (change in lift rate, load handled, lift height and asymmetry) during a lifting task to verify this hypothesis.

Lastly, to better understand work scheduling, future work can look at the amount of rest break required to minimize the development of fatigue after exposure to WBV or when performing repeated work at different levels of task precision. Additionally, these studies can also look at the effects of exposure time (vibration and/or repetitive lifting) to understand after what time point one starts to change their movement strategy. This would eventually allow better work scheduling strategies aimed at reducing muscle fatigue and the risk to back injury.

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7.4 Conclusion

The objective of my dissertation research was to explore the biomechanical link between physical fatigue and the development of low back pain. The underlying theory was that repetitive manual lifting tasks leads to behavioral and physiological changes that affect the risk to back injury. In doing so, this dissertation work specifically addressed the behavioral and physiological changes associated with a repetitive lifting task under low and high levels of task precision demands, and when the lifting followed exposure to

WBV.

Performing a repetitive asymmetric lifting activity for 60 minutes increased the subjective assessment of the perceived workload. While an increase in this measure suggests an increase in the overall workload experienced by the participants, the null effect observed for WBV exposure and lifting under high task precision demands indicates that an individual’s perception of the workload is dominated by repetitive stooped lifting activity.

Both studies showed 60 minutes of repetitive lifting activity to decrease tissue oxygenation levels obtained from the erector spinae muscles. This response also decreased during a prolonged seating activity (with and without vibration exposure).

Based on the existing literature that have found an association between fatigue related spectral changes in the EMG signals and tissue oxygenation measures, the results from the current studies show that prolonged seating without a backrest and a repetitive asymmetric lifting activity leads to the development of erector spinae muscle fatigue.

However, like ratings of perceived exertion, the changes in muscle physiology were

179 unaffected by whole body vibration exposure and task precision demands. The null effect seen for this measure again indicates the repetitive stooped lifting activity more heavily influenced erector spinae muscle physiology than did task precision demands or

WBV exposure.

This research has demonstrated that people adapt their movement behavior when performing repetitive manual work. Even though participants opted for different movement strategies while performing the lifting tasks, there was an overall agreement from both studies that showed an increase in forward bending motions and three dimensional movement velocities of the spine. Additionally, the lateral bending moment of the spine and lift duration decreased with repetitive asymmetric lifting task.

Moreover, these behavioral changes were associated with changes in the muscle physiology measures. This, along with larger movement variability with repetitive lifting activity suggests that these behavioral changes are coping mechanism with development of muscle fatigue. Further, an increase in the peak (95th percentile) spine kinematic and moment measures illustrates a shift in movement strategy towards a ballistic behavior when performing repeated lifting movements. Three of the five behavioral changes identified in this dissertation have also been shown to increase LBD risk in manual handling jobs. Thus, the increase in the overall magnitude of spine kinematic and moment measures suggests the link between fatigue and the increased risk to low back injury.

Although there was no interaction between WBV exposure and task demands during the repetitive lifting task, the results from study 2a and 2b provide insight to the

180 elevated injury risk associated with these physical factors. Specifically, when the repetitive lifting activity followed WBV exposure, larger twisting motions and movement velocity of the spine occurred; both are documented factors associated with increased back injury risk. The increase in asymmetric motions and movement velocity with exposure to WBV may be a compensatory mechanism to cope with spinal instability; specifically due to loss in passive and active stiffness, and increased delay in the neuromuscular response. However, larger twisting motions and velocity can increase co- activation of the trunk musculature and thereby increase spinal loading. Further, lifting under high precision demands resulted in larger lift durations, twisting motions and lateral bending moment of the spine; all of which are reported to increase spinal loading.

In addition to behavioral and physiological changes prolonged repetitive lifting lead to decrements in performing controlled spine motions in the sagittal plane.

Specifically, over time, with the development of muscle fatigue, there was an increase in the sagittal plane of motion. This increase in forward flexion during a controlled task indicates decrements in motor performance arising from repetitive lifting activity. The development of viscoelastic creep with larger motions in the sagittal plane can increase the risk of injury to the passive stabilizing structures when performing repetitive stooped lifting activity.

In conclusion, these findings can inform ergonomists, industrial and system engineers to be aware of fatigue-related shifts in movement behavior and its consequences on back injury risk especially when performing repetitive manual work for an hour.

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References

Adams, M. A., & Dolan, P. (1996). Time-dependent changes in the lumbar spine's resistance to bending. Clinical Biomechanics, 11(4), 194-200.

Andersen, J. H., Haahr, J. P., & Frost, P. (2007). Risk factors for more severe regional musculoskeletal symptoms: A two‐year prospective study of a general working population. Arthritis & Rheumatism, 56(4), 1355-1364.

Andersson, G.B.J. (1998). Epidemiology of low back pain. Acta Orthopaedica, 69: S28– S31

Arora, N., & Grenier, S. G. (2012). Acute effects of whole body vibration on directionality and reaction time latency of trunk muscles: The importance of rest and implications for spine stability. Journal of Electromyography and Kinesiology, 23(2), 394-401

Battié, M. C., Videman, T., Levalahti, E., Gill, K., & Kaprio, J. (2007). Heritability of low back pain and the role of disc degeneration. Pain, 131(3), 272-280.

Beach, T. A., Coke, S. K., & Callaghan, J. P. (2006). Upper body kinematic and low- back kinetic responses to precision placement challenges and cognitive distractions during repetitive lifting. International journal of industrial ergonomics, 36(7), 637- 650.

Bennet, D.J., Hollerbach, J.M., Xu, Y., Hunter, I.W. (1992). Time-varying stiffness of human elbow joint during cyclic voluntary movement. Experimental Brain Research, 88, 433–442.

Bergqvist, U., Wolgast, E., Nilsson, B., & Voss, M. (1995). Musculoskeletal disorders among visual display terminal workers: individual, ergonomic, and work organizational factors. Ergonomics, 38(4), 763-776.

Bernard, B. (1997). Musculoskeletal Disorders and Workplace Factors. A Critical Review of Epidemiologic Evidence for Work-related Musculoskeletal Disorders of the Neck, Upper Extremity, and Low Back. National Institute for Occupational Safety and Health, Cincinnati.

182

Bigos, S. J., Battie, M. C., Spengler, D. M., Fisher, L. D., Fordyce, W. E., Hansson, T. H., & Wortley, M. D. (1991). A prospective study of work perceptions and psychosocial factors affecting the report of back injury. Spine,16(1), 1-6.

Bonato, P., Ebenbichler, G., Roy, S., Lehr, S., Posch, M., Kollmitzer, J., Della Croce U. (2003). Muscle fatigue and fatigue-related biomechanical changes during a cyclic lifting task. Spine, 28(16), 1810-1820.

Bonato, P., Boissy, P., Della Croce, U., & Roy, S. H. (2002). Changes in the surface EMG signal and the biomechanics of motion during a repetitive lifting task. Neural Systems and Rehabilitation Engineering, IEEE Transaction,10(1), 38-47.

Bonato, P., Roy, S. H., Knaflitz, M., & De Luca, C. J. (2001). Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions. Biomedical Engineering, IEEE Transactions on, 48(7), 745-753.

Bongers, P. M., de Winter, C. R., Kompier, M. A., & Hildebrandt, V. H. (1993). Psychosocial factors at work and musculoskeletal disease. Scandinavian journal of work, environment & health, 297-312.

Bootsma, R. J., Fernandez, L., & Mottet, D. (2004). Behind Fitts’ law: kinematic patterns in goal-directed movements. International Journal of Human-Computer Studies, 61(6), 811-821.

Borg, G. (1982). Ratings of perceived exertion and heart rates during short-term cycle exercise and their use in a new cycling strength test. International Journal of Sports Medicine, 3(3), 153-158.

Borg, G., Hassmén, P., & Lagerström, M. (1987). Perceived exertion related to heart rate and blood lactate during arm and leg exercise. European journal of applied physiology and occupational physiology, 56(6), 679-685.

Borg, G., Ljunggren, G., & Ceci, R. (1985). The increase of perceived exertion, aches and pain in the legs, heart rate and blood lactate during exercise on a bicycle ergometer. European journal of applied physiology and occupational physiology, 54(4), 343-349.

Bovenzi, M, & Hulshof, C. T. (1999). An updated review of epidemiologic studies on the relationship between exposure to whole-body vibration and low back pain (1986- 1997). International archives of occupational and environmental health, 72(6), 351- 65.

183

Bovenzi, M. (2010). A longitudinal study of low back pain and daily vibration exposure in professional drivers. Industrial health, 48(5), 584-595.

Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2012-13 Edition, Heavy and Tractor-trailer Truck Drivers, on the Internet at http://www.bls.gov/ooh/transportation-and-material-moving/heavy-and-tractor- trailer-truck-drivers.htm

Cann, A. P., Salmoni, A. W., & Eger, T. R. (2004). Predictors of whole-body vibration exposure experienced by highway transport truck operators. Ergonomics, 47(13), 1432-53.

Capodaglio, E. M. (2001). Comparison between the CR10 Borg's scale and the VAS (visual analogue scale) during an arm-cranking exercise. Journal of occupational rehabilitation, 11(2), 69-74.

Carayon, P., Smith, M. J., & Haims, M. C. (1999). Work organization, job stress, and work-related musculoskeletal disorders. Human Factors: The Journal of the Human Factors and Ergonomics Society, 41(4), 644-663.

Carlsöö, S. (1982). The effect of vibration on the skeleton, joints and muscles: A review of the literature. Applied ergonomics, 13(4), 251-258.

Castiello, U., Bennett, K., & Stelmach, G. E. (1993). The bilateral reach to grasp movement. Behavioural brain research, 56(1), 43-57.

Chaffin, D. B. (1987). Manual materials handling and the biomechanical basis for prevention of low-back pain in industry—an overview. The American Industrial Hygiene Association Journal, 48(12), 989-996.

Chen, Y.L. (2000). Changes in lifting dynamics after localized arm fatigue. International Journal of Industrial Ergonomics, 25(6), 611-619.

Cholewicki, J., Silfies, S. P., Shah, R. A., Greene, H. S., Reeves, N. P., Alvi, K., & Goldberg, B. (2005). Delayed trunk muscle reflex responses increase the risk of low back injuries. Spine, 30(23), 2614-2620

Coutts, A. J., Rampinini, E., Marcora, S. M., Castagna, C., & Impellizzeri, F. M. (2009). Heart rate and blood lactate correlates of perceived exertion during small-sided soccer games. Journal of Science and Medicine in Sport, 12(1), 79-84.

Cresswell, A. G., & Thorstensson, A. (1994). Changes in intra-abdominal pressure, trunk muscle activation and force during isokinetic lifting and lowering. European journal of applied physiology and occupational physiology, 68(4), 315-321. 184

Dagenais, S., Caro, J., Haldeman, S. (2008). A systematic review of low back pain cost of illness studies in the United States and internationally. Spine J. 8, 8–20

Davis, K. G., & Marras, W. S. (2000). Assessment of the relationship between box weight and trunk kinematics: Does a reduction in box weight necessarily correspond to a decrease in spinal loading?. Human Factors: The Journal of the Human Factors and Ergonomics Society, 42(2), 195-208.

Davis, K. G., & Marras, W. S. (2003). Partitioning the contributing role of biomechanical, psychosocial, and individual risk factors in the development of spine loads. The Spine Journal, 3(5), 331-338.

Davis, K. G., Marras, W. S., Heaney, C. A., Waters, T. R., & Gupta, P. (2002). The impact of mental processing and pacing on spine loading: 2002 Volvo Award in biomechanics. Spine, 27(23), 2645-2653. Davis, K., & Marras, W. (2005). Load spatial pathway and spine loading: how does lift origin and destination influence low back response?. Ergonomics,48(8), 1031-1046.

Davis, K.G., Marras, W.S. (2000). The effects of motion on trunk biomechanics. Clinical Biomechanics, 15, 703–717.

De Luca, C. J. (1997). The use of surface electromyography in biomechanics. Journal of applied biomechanics, 13, 135-163.

De Luca, C. J. (1984). Myoelectrical manifestations of localized muscular fatigue in humans. Critical reviews in biomedical engineering, 11(4), 251. de Oliveira, C. G., Simpson, D. M., & Nadal, J. (2001). Lumbar back muscle activity of helicopter pilots and whole-body vibration. Journal of biomechanics,34(10), 1309- 1315.

Dedering, A., Németh, G., & Harms-Ringdahl, K. (1999). Correlation between electromyographic spectral changes and subjective assessment of lumbar muscle fatigue in subjects without pain from the lower back. Clinical biomechanics, 14(2), 103.

Dempsey, P.G. (1998). A critical review of biomechanical, epidemiological, physiological and psychophysical criteria for designing manual materials handling tasks. Ergonomics, 41 (1), 73 – 88.

Devereux, J. J., Buckle, P. W., & Vlachonikolis, I. G. (1999). Interactions between physical and psychosocial risk factors at work increase the risk of back disorders: an

185

epidemiological approach. Occupational and Environmental Medicine, 56(5), 343- 353.

Dolan, P. and Adams, M.A. (1993). The relation between EMG activity and extensor moment generation in the erector spinae muscles during bending and lifting activities. Journal of Biomechanics, 26(4-5), 513–22.

Dolan, P. and Adams, M.A. (1998). Repetitive lifting tasks fatigue the back muscles and increase the bending moment acting on the lumbar spine. Journal of Biomechanics, 31(8), 713-721.

Dolan, P. and Adams, M.A. (2001). Recent advances in lumbar spinal mechanics and their significance for modeling. Clinical Biomechanics, 16,(S1), S8-S16.

Dolan, P., Kingma, I., De Looze, M. P., van Dieen, J. H., Toussaint, H. M., Baten, C. T. M., & Adams, M. A. (2001). An EMG technique for measuring spinal loading during asymmetric lifting. Clinical Biomechanics, 16, S17-S24.

Dolan, P., Mannion, A. F., & Adams, M. A. (1994). Passive tissues help the back muscles to generate extensor moments during lifting. Journal of biomechanics, 27(8), 1077- 1085.

Dolan, P., Mannion, A. F., & Adams, M. A. (1995). Fatigue of the erector spinae muscles: A quantitative assessment using" frequency banding" of the surface electromyography signal. Spine, 20(2), 149-159.

Drury, C. G. (1985). Influence of restricted space on manual materials handling. Ergonomics, 28(1), 167-175.

Duncan, N.A. and Ahmed, A. M. (1991). The role of axial rotation in the etiology of unilateral disc prolapse: an experimental and finite-element analysis. Spine, 16(9), 1089-1098.

Dupeyron, A., Perrey, S., Micallef, J. P., & Pélissier, J. (2010). Influence of back muscle fatigue on lumbar reflex adaptation during sudden external force perturbations. Journal of Electromyography and Kinesiology, 20(3), 426-432.

Ekström, L., Kaigle, a, Hult, E., Holm, S., Rostedt, M., & Hansson, T. (1996). Intervertebral disc response to cyclic loading--an animal model. Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine, 210(4), 249-58.

186

El Falou, W., Duchêne, J., Grabisch, M., Hewson, D., Langeron, Y., & Lino, F. (2003(1996).. Evaluation of driver discomfort during long-duration car driving. Applied ergonomics, 34(3), 249-255.

Falla, D., & Farina, D. (2007). Periodic increases in force during sustained contraction reduce fatigue and facilitate spatial redistribution of trapezius muscle activity. Experimental Brain Research, 182(1), 99-107.

Farina, D., Leclerc, F., Arendt-Nielsen, L., Buttelli, O., & Madeleine, P. (2008). The change in spatial distribution of upper trapezius muscle activity is correlated to contraction duration. Journal of Electromyography and Kinesiology, 18(1), 16-25.

Feltham, M.G., van Dieen, J.H., Coppieters, M.W., Hodges, P.W. (2006). Changes in joint stability with muscle contraction measured from transmission of mechanical vibration. Journal of Biomechanics, 39(15), 2850-6.

Ferguson, S. A., & Marras, W. S. (1997). A literature review of low back disorder surveillance measures and risk factors. Clinical Biomechanics, 12(4), 211-226.

Ferguson, S. A., Allread, W. G., Le, P., Rose, J., & Marras, W. S. (2013). Shoulder Muscle Fatigue During Repetitive Tasks as Measured by Electromyography and Near-Infrared Spectroscopy. Human Factors: The Journal of the Human Factors and Ergonomics Society.

Ferrari, M., Mottola, L., & Quaresima, V. (2004). Principles, techniques, and limitations of near infrared spectroscopy. Canadian Journal of Applied Physiology, 29(4), 463- 487.

Fitts, P. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of experimental psychology,47(6), 381.

Fitts, R. H., & Widrick, J. J. (1996). Muscle mechanics: adaptations with exercise- training. Exercise and sport sciences reviews, 24(1), 427-474.

Fraser, D., Potvin, J., Jones, J. (2000). Effects of trunk muscle fatigue on spine mechanics during repetitive asymmetrical lifting. Proceedings of the XIVth Triennial Congress of the International Ergonomics Association and 44th Annual Meeting of the Human Factors and Ergonomics Society, San Diego, CA

Frymoyer, J., Pope, M., Costanza, M., Rosen, J., Goggin, J., Wilder, D. (1980). Epidemiologic studies of low-back pain. Spine 5, 419–442.

187

Frymoyer, J. W., Pope, M. H., Clements, J. H., Wilder, D. G., MacPherson, Brian., & Ashikaga, Takamaru. (1983). Risk factors in low-back pain. An epidemiological survey. The Journal of bone and joint surgery. American volume, 65(2), 213-8.

Fuller, J. R., Fung, J., & Côté, J. N. (2011). Time-dependent adaptations to posture and movement characteristics during the development of repetitive reaching induced fatigue. Experimental Brain Research, 211(1), 133-143.

Gandevia, S. C. (2001). Spinal and supraspinal factors in human muscle fatigue. Physiological reviews, 81(4), 1725-1789.

Garg, A. and Banaag, J. (1988). Maximum acceptable weights, heart rates and RPEs for one hour’s repetitive asymmetric lifting. Ergonomics, 31(1), 77–96

Garg, A., & Herrin, G. D. (1979). Stoop or squat: A biomechanical and metabolic evaluation. AIIE transactions, 11(4), 293-302.

Gates, D. H., & Dingwell, J. B. (2011). The effects of muscle fatigue and movement height on movement stability and variability. Experimental Brain Research, 209(4), 525-536.

Granacher, U., Gruber, M., Forderer, D., Strass, D., Gollhofer, A. (2010). Effects of ankle fatigue on functional reflex activity during gait perturbations in young and elderly men. Gait Posture, 32 (1), 107-112

Granata, K. P., Marras, W. S., & Davis, K. G. (1999). Variation in spinal load and trunk dynamics during repeated lifting exertions. Clinical Biomechanics,14(6), 367- 375.

Granata, K. P. and Gottipati, P. (2008). Fatigue influences dynamic stability of the torso. Ergonomics, 51 (8), 1258-71

Granata, K. P., & Marras, W. S. (1995). An EMG-assisted model of trunk loading during free-dynamic lifting. Journal of Biomechanics, 28(11), 1309-1317.

Granata, K. P., & Marras, W. S. (1995). The influence of trunk muscle coactivity on dynamic spinal loads. Spine, 20(8), 913-919.

Granata, K. P., Rogers, E., & Moorhouse, K. (2005). Effects of static flexion–relaxation on paraspinal reflex behavior. Clinical Biomechanics, 20(1), 16-24.

Granata, K. P., Slota, G. P., & Wilson, S. E. (2004). Influence of fatigue in neuromuscular control of spinal stability. Human Factors: The Journal of the Human Factors and Ergonomics Society, 46(1), 81-91. 188

Granata, K.P. and England, S.A. (2006). Stability of dynamic trunk movement. Spine, 31(10), E271–E276.

Granata, K.P. and Marras, W.S. (2000). Cost–Beneﬁt of Muscle Cocontraction in Protecting against Spinal Instability. Spine. 25(11), 1398-1404.

Granata, K.P. and Wilson, S.E. (2001). Trunk posture and spinal stability. Journal of Biomechanics. 16 (8), 650–659.

Gregory, D. E., and Callaghan, J. P. (2011). Does Vibration Influence the Initiation of Intervertebral Disc Herniation? Spine, 2011, 36(4), E225-E231.

Gregory, D.E., Narula, S., Howarth, S.J., Russell, C., Callaghan, J.P. (2008). The effect of fatigue on trunk muscle activation patterns and spine postures during simulated firefighting tasks. Ergonomics, 51(7), 1032-41

Hamaoka, T., McCully, K. K., Quaresima, V., Yamamoto, K., & Chance, B. (2007). Near-infrared spectroscopy/imaging for monitoring muscle oxygenation and oxidative metabolism in healthy and diseased humans. Journal of biomedical optics, 12(6), 062105-062105

Hansson, T., Magnusson, M., & Broman, H. (1991). Back muscle fatigue and seated whole body vibrations: an experimental study in man. Clinical Biomechanics, 6(3), 173-178.

Heneweer, H., Staes, F., Aufdemkampe, G., van Rijn, M., Vanhees, M. (2011). Physical activity and low back pain: a systematic review of recent literature. European Spine Journal, 20(6), 826-45

Herrmann, C. M., Madigan, M. L., Davidson, B. S., & Granata, K. P. (2006). Effect of lumbar extensor fatigue on paraspinal muscle reflexes. Journal of Electromyography and Kinesiology, 16(6), 637-641.

Heuch, I., Hagen, K., Heuch, I., Nygaard, Ø., & Zwart, J. A. (2010). The impact of body mass index on the prevalence of low back pain: the HUNT study. Spine,35(7), 764- 768.

Hinz, B., Seidel, H., Menzel, G., & Blüthner, R. (2002). Effects related to random whole- body vibration and posture on a suspended seatwith and without backrest. Journal of Sound and Vibration, 253(1), 265-282.

Hoogendoorn, W. E., Bongers, P. M., De Vet, H. C. W., Ariens, G. A. M., Van Mechelen, W., & Bouter, L. M. (2002). High physical work load and low job 189

satisfaction increase the risk of sickness absence due to low back pain: results of a prospective cohort study. Occupational and Environmental Medicine, 59(5), 323-328.

Hughes, R.E., Silverstein, B.A., and Evanoff, B.A. (1997). Risk factors for work-related musculoskeletal disorders in an aluminum smelter. American Journal of Industrial Medicine, 32(1), 66–75

Hummel, A., Läubli, T., Pozzo, M., Schenk, P., Spillmann, S., & Klipstein, A. (2005). Relationship between perceived exertion and mean power frequency of the EMG signal from the upper trapezius muscle during isometric shoulder elevation. European journal of applied physiology, 95(4), 321-326.

Hurwitz, E. L., & Morgenstern, H. (1997). Correlates of back problems and back-related disability in the United States. Journal of clinical epidemiology,50(6), 669-681.

Jensen, B. R., Schibye, B., Søgaard, K., Simonsen, E. B., & Sjøgaard, G. (1993). Shoulder muscle load and muscle fatigue among industrial sewing-machine operators. European journal of applied physiology and occupational physiology, 67(5), 467-475.

Kelaher, D. (2006). Effects of Trunk Extensor Muscle Fatigue on Trunk Proprioception and Biomechanics. PhD diss., North Carolina State University.

Keller, T. S., & Nathan, M. (1999). Height change caused by creep in intervertebral discs: a sagittal plane model. Journal of Spinal Disorders & Techniques, 12(4), 313- 324.

Kim, S.H. and Chung, M.K. (1995). Eﬀects of posture, weight and frequency on trunk muscular activity and fatigue during repetitive lifting tasks. Ergonomics, 38 (5), 853– 863.

Kimura, M., Sato, H., Ochi, M., Hosoya, S., & Sadoyama, T. (2007). Electromyogram and perceived fatigue changes in the trapezius muscle during typewriting and recovery. European journal of applied physiology, 100(1), 89-96.

Kopec, J. A., Sayre, E. C., & Esdaile, J. M. (2004). Predictors of back pain in a general population cohort. Spine, 29(1), 70-77.

Kroemer, E. (1992). Personnel training for safer material handling. Ergonomics, 35(9), 1119-1134.

Kroemer, K.H and Marras, W.S. (1981). Evaluation of maximal and submaximal static muscle exertions. Human Factors, 23(6), 643-653

190

Kumar, S. (1984). The physiological cost of three different methods of lifting in sagittal and lateral planes. Ergonomics, 27(4), 425-433.

Kumar, S. (1990). Cumulative load as a risk factor for back pain. Spine,15(12), 1311- 1316.

Kumar, S. (1997). The effect of sustained spinal load on intra-abdominal pressure and EMG characteristics of trunk muscles. Ergonomics, 40(12), 1312-1334.

Laursen, B., Jensen, B. R., & Sjøgaard, G. (1998). Effect of speed and precision demands on human shoulder muscle electromyography during a repetitive task. European journal of applied physiology and occupational physiology, 78(6), 544-548.

Lavender, S. A., Andersson, G. B., Schipplein, O. D., & Fuentes, H. J. (2003). The effects of initial lifting height, load magnitude, and lifting speed on the peak dynamic L5/S1 moments. International Journal of Industrial Ergonomics, 31(1), 51-59.

Lavender, S. A., Li, Y. C., Andersson, G. B. J., & Natarajan, R. N. (1999). The effects of lifting speed on the peak external forward bending, lateral bending, and twisting spine moments. Ergonomics, 42(1), 111-125.

Lavender, S. A., Marras, W. S., Ferguson, S. A., Splittstoesser, R. E., Yang, G. (2012). Developing physical exposure based back injury risk models applicable to manual handling jobs in distribution center. Journal of Occupational and Enviornmental Hygiene, 9, 450-459

Lavender, S. A., Tsuang, Y. H., Andersson, G. B. J., Hafezi, A., & Shin, C. C. (1992). Trunk muscle cocontraction: the effects of moment direction and moment magnitude. Journal of orthopaedic research, 10(5), 691-700.

Lee, J. and Nussbaum, M.A. (2012). Experienced workers exhibit distinct torso kinematics/kinetics and patterns of task dependency during repetitive lifts and lowers. Ergonomics, 55(12), 1535-47.

Li, L., Lamis, F., & Wilson, S. E. (2008). Whole-body vibration alters proprioception in the trunk. International Journal of Industrial Ergonomics,38(9), 792-800.

Li, K. W., & Lee, C. (1999). Postural analysis of four jobs on two building construction sites: an experience of using the OWAS method in Taiwan. Journal of Occupational Health –English Edition, 41, 183-190

Lin, D., Nussbaum, M.A., Madigan, M.L. (2012). Efficacy of three interventions at mitigating the adverse effects of muscle fatigue on postural control. Ergonomics, 55(1), 103-113 191

Looze, M. D., Bosch, T., & Dieën, J. V. (2009). Manifestations of shoulder fatigue in prolonged activities involving low-force contractions. Ergonomics,52(4), 428-437.

Lötters, F., Burdorf, A., Kuiper, J., & Miedema, H. (2003). Model for the work- relatedness of low-back pain. Scandinavian journal of work, environment & health, 431-440.

Lotz, C., Agnew, M., Godwin, A., & Stevenson, J. (2009). The effect of an on-body Personal Lift-Assist Device (PLAD) on fatigue during a repetitive lifting task. Journal of Electromyography and Kinesiology, 19(2), 331–340.

Luo, X., Pietrobon, R., S, X. S., Liu, G. G., & Hey, L. (2004). Estimates and patterns of direct health care expenditures among individuals with back pain in the United States. Spine, 29.

Macfarlane, G.J., Thomas, E., Papageorgiou, A.C., Croft, P.R., Jayson, M.I., Silman, A.J. (1997). Employment and physical work activities as predictors of future low back pain. Spine, 22(10),1143- 9.

MacGregor, A. J., Andrew, T., Sambrook, P. N., & Spector, T. D. (2004). Structural, psychological, and genetic influences on low back and neck pain: a study of adult female twins. Arthritis Care & Research, 51(2), 160-167.

MacKenzie, C. L., Marteniuk, R. G., Dugas, C., Liske, D., & Eickmeier, B. (1987). Three-dimensional movement trajectories in Fitts' task: implications for control. The Quarterly Journal of Experimental Psychology, 39(4), 629-647.

Madeleine, P., Voigt, M., & Mathiassen, S. E. (2008). The size of cycle-to-cycle variability in biomechanical exposure among butchers performing a standardised cutting task. Ergonomics, 51(7), 1078-1095.

Magnusson, M., Almqvist, M., Broman, H., Pope, M., & Hansson, T. (1992). Measurement of height loss during whole body vibrations. Journal of Spinal Disorders & Techniques, 5(2), 198-203.

Magnusson, M. L., Pope, M. H., Wilder, D. G., & Areskoug, B. (1996). Are occupational drivers at an increased risk for developing musculoskeletal disorders?. Spine, 21(6), 710-717.

Maikala, R. V., & Bhambhani, Y. N. (2006). In vivo lumbar erector spinae oxygenation and blood volume measurements in healthy men during seated whole‐body vibration. Experimental physiology, 91(5), 853-866.

192

Maikala, R. V., & Bhambhani, Y. N. (2008). Functional changes in cerebral and paraspinal muscle physiology of healthy women during exposure to whole-body vibration. Accident Analysis & Prevention, 40(3), 943-953.

Mancini, D. M., Bolinger, L., Li, H., Kendrick, K., Chance, B., & Wilson, J. R. (1994). Validation of near-infrared spectroscopy in humans. Journal of Applied Physiology, 77(6), 2740-2747.

Manning, D. P., Mitchell, R. G., & Blanchfield, L. P. (1984). Body movements and events contributing to accidental and nonaccidental back injuries. Spine,9(7), 734-739

Marras, W. S. (2008). The working back. John Wiley & Sons.

Marras, W. S., & Davis, K. G. (1998). Spine loading during asymmetric lifting using one versus two hands. Ergonomics, 41(6), 817-834.

Marras, W. S., & Granata, K. P. (1997). The development of an EMG-assisted model to assess spine loading during whole-body free-dynamic lifting. Journal of Electromyography and Kinesiology, 7(4), 259-268.

Marras, W. S., & Granata, K. P. (1995). A biomechanical assessment and model of axial twisting in the thoracolumbar spine. Spine, 20(13), 1440-1451.

Marras, W. S., & Mirka, G. A. (1990). Muscle activities during asymmetric trunk angular accelerations. Journal of orthopaedic research, 8(6), 824-832.

Marras, W. S., & Sommerich, C. M. (1991). A three-dimensional motion model of loads on the lumbar spine: II. Model validation. Human Factors: The Journal of the Human Factors and Ergonomics Society, 33(2), 139-149.

Marras, W. S., Davis, K. G., Heaney, C. A., Maronitis, A. B., & Allread, W. G. (2000). The influence of psychosocial stress, gender, and personality on mechanical loading of the lumbar spine. Spine, 25(23), 3045-3054.

Marras, W. S., Davis, K. G., Kirking, B. C., & Granata, K. P. (1999). Spine loading and trunk kinematics during team lifting. Ergonomics, 42(10), 1258-1273.

Marras, W. S., Granata, K. P., Davis, K. G., Allread, W. G., & Jorgensen, M. J. (1997). Spine loading and probability of low back disorder risk as a function of box location on a pallet. Human Factors and Ergonomics in Manufacturing,7(4), 323-336.

Marras, W. S., Granata, K. P., Davis, K. G., Allread, W. G., & Jorgensen, M. J. (1999). Effects of box features on spine loading during warehouse order selecting. Ergonomics, 42(7), 980-996. 193

Marras, W. S., Lavender, S. A., Ferguson, S. A., Splittstoesser, R. E., & Yang, G. (2010). Quantitative dynamic measures of physical exposure predict low back functional impairment. Spine, 35(8), 914-923.

Marras, W.S. and Granata, K.P. (1997). Changes in trunk dynamics and spine loading during repeated trunk exertions. Spine, 22(21), 2564–70.

Marras, W.S., Lavender, S., Leurgans, S., Fathallah, F., Ferguson, S., Allread, G., et al., (1995a). Biomechanical risk factors for occupationally related low back disorders. Ergonomics 38, 337–410.

Marras, W.S., Lavender, S.A., Leurgans, S.E., Rajulu, S.L., Allread, W.G., Fathallah, F.A., Ferguson, S.A. (1993a). The role of dynamic three-dimensional trunk motion in occupationally-related low back disorders. The effects of workplace factors, trunk position, and trunk motion characteristics on risk of injury. Spine, 18(5), 617-628

Marras, W.S., Mirka, G.A. (1993b). Electromyographic studies of the lumbar trunk musculature during the generation of low-level trunk acceleration. Journal of Orthopaedic Research 11(6),811–7.

Marras, W.S., Parakkat, J., Chany, A.M., Yang, G., Burr, D., Lavender, S.A. (2006). Spine loading as a function of lift frequency, exposure duration and work experience. Clinical Biomechanics. 21(4), 345–352.

Marteniuk, R. G., MacKenzie, C. L., Jeannerod, M., Athenes, S., & Dugas, C. (1987). Constraints on human arm movement trajectories. Canadian Journal of Psychology/Revue canadienne de psychologie, 41(3), 365.

Mawston, G.A., McNair, P.J., Boocock, M.G. (2007). The effects of prior warning and lifting-induced fatigue on trunk muscle and postural responses to sudden loading during manual handling, Ergonomics, 50(12), 2157-70

McGill, S. M. (1996). Searching for the safe biomechanical envelope for maintaining healthy tissue. Pre-ISSLS Workshop: The Contribution of Biomechanics to the Prevention and Treatment of Low Back Pain, University of Vermont, 25 June.

McGill, S. M., Hughson, R. L., & Parks, K. (2000). Lumbar erector spinae oxygenation during prolonged contractions: implications for prolonged work. Ergonomics, 43(4), 486-493.

Mehta, J.P., Lavender, S.A, Jagacinski, R.J. (2014). Physiological and Biomechanical Responses to a Prolonged Repetitive Asymmetric Lifting Activity. Ergonomics, (in press) 194

Messier, J., Adamovich, S., Berkinblit, M., Tunik, E., Poizner, H. (2003). Inﬂuence of movement speed on accuracy and coordination of reaching movements to memorized targets in three-dimensional space in a deafferented subject. Experimental Brain Research, 150(4),399–416

Mikkonen, P., Viikari-Juntura, E., Remes, J., Pienimaki, T., Solovieva, S., Taimela, S., Zitting, P., Koiranen, M., Leino-Arjas, P., Karppinen, J. (2012). Physical workload and risk of low back pain in adolescence. Occupational and Environmental Medicine, 69(4), 284-90

Mirka, G. A., & Marras, W. S. (1993). A stochastic model of trunk muscle coactivation during trunk bending. Spine, 18(11), 1396-1409.

Miura, H., Araki, H., Matoba, H., & Kitagawa, K. (2000). Relationship among oxygenation, myoelectric activity, and lactic acid accumulation in vastus lateralis muscle during exercise with constant work rate. International journal of sports medicine, 21(03), 180-184.

Miyamoto, M., Shirai, Y., Nakayama, Y., Gembun, Y., & Kaneda, K. (2000). An epidemiologic study of occupational low back pain in truck drivers. Journal of Nippon Medical School, 67(3), 186-190.

Moorhouse, K. M., & Granata, K. P. (2007). Role of reflex dynamics in spinal stability: intrinsic muscle stiffness alone is insufficient for stability. Journal of biomechanics, 40(5), 1058-1065.

Moritani, T., Nagata, A., & Muro, M. (1982). Electromyographic manifestations of muscular fatigue. Medicine and science in sports and exercise, 14(3), 198.

Murthy, G., Kahan, N., Hargens, A., Rempel, D. (1997). Forearm muscle oxygenation decreases with low levels of voluntary contraction. Journal of Orthopaedic Research, 15(4), 507–511

Naeije, M., & Zorn, H. (1982). Relation between EMG power spectrum shifts and muscle fibre action potential conduction velocity changes during local muscular fatigue in man. European Journal of Applied Physiology and Occupational Physiology, 50(1), 23-33.

Nardone, A., Tarantola, J., Giordano, A., & Schieppati, M. (1997). Fatigue effects on body balance. Electroencephalography and Clinical Neurophysiology/Electromyography and Motor Control, 105(4), 309-320.

195

National Academy of Science. (2001). Musckuloskeletal disorders and the workplace: Low back and upper extremities. Washington DC: National Academy Press.

Neely, G., Ljunggren, G., Sylvén, C., & Borg, G. (1992). Comparison between the Visual Analogue Scale (VAS) and the Category Ratio Scale (CR-10) for the evaluation of leg exertion. International journal of sports medicine, 13(02), 133-136.

Nielsen, P. K., Andersen, L., & Jørgensen, K. (1998). The muscular load on the lower back and shoulders due to lifting at different lifting heights and frequencies. Applied Ergonomics, 29(6), 445-450.

O'Brien PR, Potvin JR. (1997). Fatigue-related EMG responses of trunk muscles to a prolonged, isometric twist exertion. Clinical Biomechanics, 12,306-13

Okunribido, O. O.; Magnusson, M. & Pope, M. H. (2008). The role of whole body vibration, posture and manual materials handling as risk factors for low back pain in occupational drivers. Ergonomics, 51, 308-329.

Palmer, K. T., Griffin, M. J., Syddall, H. E., Pannett, B., Cooper, C., & Coggon, D. (2003). The relative importance of whole body vibration and occupational lifting as risk factors for low-back pain. Occupational and Environmental Medicine, 60(10), 715-721.

Panjabi, M. M., Andersson, G. B. J., Jorneus, L., Hult, E., & Mattsson, L. (1986). In vivo measurements of spinal column vibrations. The Journal of Bone and Joint Surgery. American Volume, 68(5), 695-702

Panjabi, M. M. (1992). The stabilizing system of the spine. Part I. Function, dysfunction, adaptation, and enhancement. Journal of Spinal Disorders & Techniques, 5(4), 383- 389.

Parkinson, R. J., Beach, T. A., & Callaghan, J. P. (2004). The time-varying response of the in vivo lumbar spine to dynamic repetitive flexion. Clinical Biomechanics, 19(4), 330-336.

Parnianpour, M., Nordin, M., Kahanovitz, N., Frankel, V. (1988). The triaxial coupling of torque generation of trunk muscles during isometric exertions and the effect of fatiguing isoinertial movements on the motor output and movement patterns. Spine, 13(9), 982-92.

Perrey, S., Thedon, T., & Rupp, T. (2010). NIRS in ergonomics: its application in industry for promotion of health and human performance at work. International Journal of Industrial Ergonomics, 40(2), 185-189.

196

Petrofsky, J. S., & Lind, A. R. (1980). The influence of temperature on the amplitude and frequency components of the EMG during brief and sustained isometric contractions. European Journal of Applied Physiology and Occupational Physiology, 44(2), 189-200.

Plamondon, A., Lariviere, C., Delisle, A., Dennis, D., Gagnon, D. (2012). Relative importance of expertise, lifting height and weight lifted on posture and lumbar external loading during a transfer task in manual handling. Ergonomics, 55(1), 85- 102.

Pope, M. H., Wilder, D. G., & Magnusson, M. (1998). Possible mechanisms of low back pain due to whole-body vibration. Journal of Sound and Vibration, 215(4), 687-697.

Pope, M. H., Goh, K. L., & Magnusson, M. L. (2002). Spine ergonomics. Annual review of Biomedical Engineering, 4(1), 49-68.

Potvin, J. R., & O'brien, P. R. (1998). Trunk muscle co-contraction increases during fatiguing, isometric, lateral bend exertions: possible implications for spine stability. Spine, 23(7), 774-780.

Potvin, J. R., & Norman, R. W. (1993). Quantification of erector spinae muscle fatigue during prolonged, dynamic lifting tasks. European Journal of Applied Physiology and Occupational Physiology, 67(6), 554-562.

Praagman, M., Veeger, H. E. J., Chadwick, E. K. J., Colier, W. N. J. M., & Van Der Helm, F. C. T. (2003). Muscle oxygen consumption, determined by NIRS, in relation to external force and EMG. Journal of Biomechanics, 36(7), 905-912.

Punnett, L., Fine, L. J., Keyserling, W. M., Herrin, G. D., & Chaffin, D. B. (1991). Back disorders and nonneutral trunk postures of automobile assembly workers. Scandinavian Journal of Work, Environment & Health, 337-346

Punnett, L., Prüss‐Ütün, A., Nelson, D. I., Fingerhut, M. A., Leigh, J., Tak, S., & Phillips, S. (2005). Estimating the global burden of low back pain attributable to combined occupational exposures. American Journal of Industrial Medicine,48(6), 459-469.

Radebold, A., Cholewicki, J., Polzhofer, G. K., & Greene, H. S. (2001). Impaired postural control of the lumbar spine is associated with delayed muscle response times in patients with chronic idiopathic low back pain. Spine, 26(7), 724-730.

Reeves, N. P., Cholewicki, J., Milner, T., & Lee, A. S. (2008). Trunk antagonist co- activation is associated with impaired neuromuscular performance. Experimental Brain Research, 188(3), 457-463.

197

Robb, M. J. M., & Mansfield, N. J. (2007). Self-reported musculoskeletal problems amongst professional truck drivers. Ergonomics, 50(6), 814-27.

Rogers, E. L., & Granata, K. P. (2006). Disturbed paraspinal reflex following prolonged flexion-relaxation and recovery. Spine, 31(7), 839.

Rolfe, P. (2000). In vivo near-infrared spectroscopy. Annual Review of Biomedical Engineering, 2(1), 715-754.

San Tho, K., Németh, G., Lamontagne, M., & Eriksson, E. (1997). Electromyographic analysis of muscle fatigue in anterior cruciate ligament deficient knees. Clinical Orthopaedics and Related Research, 340, 142-151

Sánchez-Zuriaga, D., Adams, M. A., & Dolan, P. (2010). Is activation of the back muscles impaired by creep or muscle fatigue?. Spine, 35(5), 517-525.

Santos, B.R., Lariviere, C., Delisle, A., Plamondon, A., Boileau, P. E., Imbeau, D. (2008). A laboratory study to quantify the biomechanical responses to whole-body vibration: the inﬂuence on balance, reﬂex response, muscular activity and fatigue. International Journal of Industrial Ergonomics, 38, 626–639.

Seliga, R., Bhattacharya, A., Succop, P., Wickstrom, R., Smith, D., & Willeke, K. (1991). Effect of workload and respirator wear on postural stability, heart rate and perceived exertion. The American Industrial Hygiene Association Journal, 52(10), 417-422.

Shan, X., Ning, X., Chen, Z., Ding, M., Shi, W., & Yang, S. (2013). Low back pain development response to sustained trunk axial twisting. European Spine Journal, 1-7.

Shin, G., D’Souza, C., & Liu, Y. H. (2009). Creep and fatigue development in the low back in static flexion. Spine, 34(17), 1873-1878.

Shiri, R., Karppinen, J., Leino-Arjas, P., Solovieva, S., & Viikari-Juntura, E. (2010a). The association between smoking and low back pain: a meta-analysis.The American Journal of Medicine, 123(1), 87-e7.

Shiri, R., Karppinen, J., Leino-Arjas, P., Solovieva, S., & Viikari-Juntura, E. (2010b). The association between obesity and low back pain: a meta-analysis. American Journal of Epidemiology, 171(2), 135-154.

Silva, P.L., Fonseca, S.T., Ocarino, J.M., Goncalves, G.P., Mancini. M.C. (2009). Contributions of Cocontraction and Eccentric Activity to Stiffness Regulation. Journal of Motor Behaviour, 41 (3), 207-218.

198

Soderberg, G. L., & Knutson, L. M. (2000). A guide for use and interpretation of kinesiologic electromyographic data. Physical Therapy, 80(5), 485-498.

Solomonow, M., Zhou, B. H., Baratta, R. V., Lu, Y., & Harris, M. (1999). Biomechanics of increased exposure to lumbar injury caused by cyclic loading: Part 1. Loss of reflexive muscular stabilization. Spine, 24(23), 2426-2434.

Sommerich, C. M., & Marras, W. S. (1992). Temporal patterns of trunk muscle activity throughout a dynamic, asymmetric lifting motion. Human Factors: The Journal of the Human Factors and Ergonomics Society, 34(2), 215-230.

Sparto, P., Parnianpour, M., Marras, W., Granata, K., Reinsel, T., Simon, S. (1997a). Neuromuscular trunk performance and spinal loading during a fatiguing isometric trunk extension with varying torque requirements. Journal of Spinal Disorders, 10(2), 145-156

Sparto, P. J., & Parnianpour, M. (1998). Estimation of trunk muscle forces and spinal loads during fatiguing repetitive trunk exertions. Spine, 23(23), 2563-2573.

Sparto, P.K., Parnianpour, M., Reinsel, T.E., Simon, S. (1996). The adaptations to fatigue during a repetitive lifting task. Biomedical Engineering Conference., Proceedings of the 1996 Fifteenth Southern, 195-196

Sparto, P.K., Parnianpour, M., Reinsel, T.E., Simon, S. (1997b). The effect of fatigue on multijoint kinematics and load sharing during a repetitive lifting test. Spine, 22(22), 2647-2654

Spurgeon, A., Gompertz, D., & Harrington, J. M. (1997). Non-specific symptoms in response to hazard exposure in the workplace. Journal of Psychosomatic Research, 43(1), 43-49.

Stambolian, D., Eltoukhy, M., Asfour, S., & Bonin, S. (2011). Investigation of Avionics Box Precision Placement Using Motion Capturing and Thermal Imaging Techniques.

Sullivan, A., & McGill, S. M. (1990). Changes in spine length during and after seated whole-body vibration. Spine, 15(12), 1257-1260.

Swinkels, A. and Dolan, P. (2000). Spinal position sense is independent of the magnitude of movement. Spine, 25(1), 98-104.

Taimela, S., Kankaanpää, M., & Luoto, S. (1999). The effect of lumbar fatigue on the ability to sense a change in lumbar position: a controlled study. Spine,24(13), 1322.

199

Trafimow, J.H., Schipplein, O.D., Novak, G.J., Andersson, G.B. (1993). The effects of quadriceps fatigue on the technique of lifting. Spine, 18(3), 364-367. van Dieën, J. H., Dekkers, J. J., Groen, V., Toussaint, H. M., & Meijer, O. G. (2001). Within-subject variability in low back load in a repetitively performed, mildly constrained lifting task. Spine, 26(16), 1799-1804. van Dieën, J. H., Vrielink, H. H. O., & Toussaint, H. M. (1993). An investigation into the relevance of the pattern of temporal activation with respect to erector spinae muscle endurance. European Journal of Applied Physiology and Occupational Physiology, 66(1), 70-75. van Dieen, J. H., Creemers, M., Draisma, I., Toussaint, H. M., & Kingma, I. (1994). Repetitive lifting and spinal shrinkage, effects of age and lifting technique. Clinical Biomechanics, 9(6), 367-374. van Dieën, J. H., Westebring-van der Putten, E. P., Kingma, I., & de Looze, M. P. (2009). Low-level activity of the trunk extensor muscles causes electromyographic manifestations of fatigue in absence of decreased oxygenation. Journal of Electromyography and Kinesiology, 19(3), 398-406. van Dieen, J.H., van der Burg, P., Raaijmakers, T. and Toussaint, H.M. (1998). Effects of Repetitive Lifting on Kinematics: Inadequate Anticipatory Control or Adaptive Changes? Journal of Motor Behavior, 30,1, 20-32.

Vandergrift, J.L., Gold, J.E., Hanlon, A., Punnett, L. (2012). Physical and psychosocial ergonomics risk factors for low back pain in automobile manufacturing workers. Occupational and Environmental Medicine, 69, 29-34

Villringer, A., Planck, J., Hock, C., Schleinkofer, L., & Dirnagl, U. (1993). Near infrared spectroscopy (NIRS): a new tool to study hemodynamic changes during activation of brain function in human adults. Neuroscience Letters, 154(1), 101-104.

Warren, N., Dillon, C., Morse, T., Hall, C., & Warren, A. (2000). Biomechanical, psychosocial, and organizational risk factors for WRMSD: population-based estimates from the Connecticut upper-extremity surveillance project (CUSP).Journal of Occupational Health Psychology, 5(1), 164.

Wilder, D. G., Aleksiev, A. R., Magnusson, M. L., Pope, M. H., Spratt, K. F., & Goel, V. K. (1996). Muscular response to sudden load: a tool to evaluate fatigue and rehabilitation. Spine, 21(22), 2628-2639.

Yamada, E., Kusaka, T., Arima, N., Isobe, K., Yamamoto, T., & Itoh, S. 2008. Relationship between muscle oxygenation and electromyography activity during 200

sustained isometric contraction. Clinical Physiology and Functional Imaging, 28(4), 216-221.

Yamazaki, S., Banes, A. J., Weinhold, P. S., Tsuzaki, M., Kawakami, M., & Minchew, J. T. (2002). Vibratory loading decreases extracellular matrix and matrix metalloproteinase gene expression in rabbit annulus cells. The spine journal: official Journal of the North American Spine Society, 2(6), 415-20.

Yang, G., Chany, A. M., Parakkat, J., Burr, D., & Marras, W. S. (2007). The effects of work experience, lift frequency and exposure duration on low back muscle oxygenation. Clinical Biomechanics, 22(1), 21-27

Yoshitake, Y., Ue, H., Miyazaki, M., Moritani, T. (2001). Assessment of lower-back muscle fatigue using electromyography, mechanomyography, and near-infrared spectroscopy. European Journal of Applied Physiology, 84 (3), 174–179

Zadry, H. R., Dawal, S. Z. M., & Taha, Z. (2011). The relation between upper limb muscle and brain activity in two precision levels of repetitive light tasks. International Journal of Occupational Safety and Ergonnomics, 17(4), 373- 384.

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Appendix A: Results from no-vibration and repetitive lifting under low precision

demands condition.

202

Table 14: p-values for the Borg rating and Tissue oxygenation measure during the seating and lifting task (VL condition).

Borg Rating Tissue Oxygenation Seating 0.003 <0.001 Lifting <0.001 <0.001

Borg rating of perceived exertion increased significantly over time during the seating and the lifting task. Muscle physiology measures obtained during the seating and the lifting task decreased significantly over time.

Table 15: p-values for the mean and standard deviation data for the spine kinematic, moment and lift duration measures during the repetitive lifting task (VL condition).

Lifting Flex Twist Lateral FBM TM LBM EV TV LBV Lift Bend Duration

Mean 0.034 0.816 0.009 0.657 0.429 <0.001 0.022 0.695 0.530 <0.001 Variability (SD) 0.227 0.400 0.414 0.831 0.178 0.019 0.768 0.991 0.088 0.003

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35 50 45 30 40

25 35 30 20 Forward Bend 25 15 Lateral Bend

degrees 20

10 15 degrees/sec Extension Vel 10 5 5 0 0 10 20 30 40 50 60 Time (minutes)

Figure 37: Changes in spine kinematics with repetitive lifting task under low demands after exposure to WBV (VL).

100 9 90 8 80 7 70 6 60 5 50 Nm 4 40 Mean 30 3 SD 20 2 10 1 0 0 10 20 30 40 50 60 Time (minutes)

Figure 38: Changes in the lateral bending moment of the spine (magnitude and standard deviation) with repetitive lifting activity under low demands after exposure to WBV (VL).

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2.5 0.20

0.18 2.0 0.16 0.14 1.5 0.12 0.10 1.0 0.08 Mean 0.06 SD 0.5 0.04 Liftduration (seconds) 0.02 0.0 0.00 10 20 30 40 50 60 Time (minutes)

Figure 39: Changes in the lift duration data (magnitude and standard deviation) with repetitive lifting activity under low demands after exposure to WBV (VL).

Table 16: p-values for the spine kinematic measures obtained in between the seating and the lifting task during the FEMAP (VL condition).

Flex Twist Lateral FBV EV TV LBV Bend Seating 0.330 0.152 0.009 0.977 0.27 0.021 0.006 Lifting 0.063 0.193 0.264 0.042 0.182 0.017 0.011

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10 40 9 35 8 30

7 6 25 5 20 Lateral Bend

degrees 4 15 TV 3 degrees/sec 10 LBV 2 1 5 0 0 Baseline 20 40 60 Time (minutes)

Figure 40: Changes in the spine kinematic data in between the seating task for the FEMAP (VL).

140 120

100 80 FBV 60 TV degrees/sec 40 LBV 20 0 10 20 30 40 50 60 Time (minutes)

Figure 41: Changes in the spine kinematic data in between the lifting task for the FEMAP (VL).

206

Appendix B: Results from correlation between oxygenated hemoglobin levels and

biomechanical measures.

207

Table 17 shows the correlation coefficients between spine kinematic and moment measures with tissue oxygenation measure obtained during each condition in Study 2.

Table 17: Correlation Coefficients between right oxygenated hemoglobin levels and spine kinematic and moment measures (bold indicate p < 0.05).

VE VD NE ND Overall Flex -0.463 -0.348 -0.248 -0.115 -0.285 Twist 0.201 -0.199 -0.252 0.003 -0.072 Lateral Bend -0.208 0.021 -0.283 0.078 -0.089 FBM -0.115 -0.053 -0.066 0.141 -0.018 TM 0.061 -0.317 -0.193 -0.417 -0.232 LBM 0.575 0.724 0.275 0.647 0.559 EV -0.116 -0.217 -0.338 -0.295 -0.246 TV -0.090 -0.375 -0.456 -0.422 -0.347 SV 0.047 -0.376 -0.665 -0.545 -0.403

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Appendix C: Settings used for whole body vibration exposure.

209

Figure 42: Screen capture for the settings used in the vibration condition.

Operating Instructions

1) Connect the output cable through panel to the platform.

2) Connect the input cable from panel to 110V, 60 Hz supply.

3) The device can be started in Manual mode or Timer mode as follows:

Manual Mode: a) Turn the Power switch to ON. The power on LED will glow. b) Set the frequency through the frequency adjustment arrow keys, and set the time via

the timer adjustment arrow keys. Push the ON button (start the device) on the front

panel. The machine on LED will glow. c) Push the OFF button (stop the device) to complete the test after desired time.

Timer Mode: 210 a) Turn the Power ON. b) Set the frequency through frequency adjustment arrow keys, and set the time to

desired duration through timer adjustment arrow keys. Push the ON button on the

front panel. The machine on LED will glow. And the timer LED will blink. c) The equipment will automatically stop after the programmed time is lapsed.

Programming the Preset Function Keys

1) Push the frequency adjustment up and down arrow keys simultaneously for few

seconds, the frequency indicator will start blinking. You can set the frequency upper

limit here; press the off button to register the frequency upper limit.

2) Move to set the time upper limit. Repeat the procedure by holding onto the timer

adjustment arrow keys simultaneously. The time indicator will blink, set the upper

limit of timer here using time up/down arrow keys. To register the timer upper limit,

press the off button.

3) The programming mode will switch to F1 key, set desired frequency and time. Press

off button to register the values to the desired keys.

4) Similarly, perform programming for other functions keys like F2, F3 and F4.

5) Finally, switch off the mains switch and restart the machine.

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Appendix D: Matlab code used to analyze biomechanical data.

212

The following Matlab code was used to identify timing markers (force scale) and extracting peaks in the spine kinematic and moment data obtained during the experiment. files = dir('*.exp'); LOUT = fopen('s02_ne_MOTION_OUTPUT_FATIGUE.XLS','w'); MARK = fopen('s02_ne_Marker.XLS','w'); fprintf(LOUT, 'm \t ID \t flex \t Ext \t twist \t side \t sideN \t flexM \t twistM \t twistMN \t sideM \t flexVN \t twistV \t twistVN \t sideV \t sideVN \t Time \n'); for m1= 1:1:length(files) test1(m1).name= importdata(files(m1).name); end;

% for m = 1:1:length(test1) for m = 1:1:(length(files)-1) % length(files);

Frame = test1(1,m).name.data(:,1); Lum_Rot = test1(1,m).name.data(:,6); Lum_Flex = test1(1,m).name.data(:,2); Lum_R_Flex = test1(1,m).name.data(:,3); FBM = test1(1,m).name.data(:,7); SBM= test1(1,m).name.data(:,9); TM= test1(1,m).name.data(:,8); FBV = test1(1,m).name.data(:,10); SBV= test1(1,m).name.data(:,12); TV= test1(1,m).name.data(:,11); TA= test1(1,m).name.data(:,14); FBA = test1(1,m).name.data(:,13); SBA= test1(1,m).name.data(:,15); lefthand = test1(1,m).name.data(:,4); righthand = test1(1,m).name.data(:,5);

% % % % % % % % % -15 -2.4 5.25 -25.2 0.33 -67.1 % % % % % % % % Lum_Flex = Lum_Flex + 15; % % % % % % % % Lum_Rot = Lum_Rot + 2.4; % % % % % % % % Lum_R_Flex = Lum_R_Flex - 5.25; % % % % % % % % FBM = FBM + 25.2; % % % % % % % % TM = TM - 0.33; % % % % % % % % SBM = SBM + 67.1; % % % % % % % % %

% fa = test1(1,m).name.data(:,14); % fb = test1(1,m).name.data(:,15); %to access %test1(1,72).name.data(5,7).....gives last file on that with point of 5th %row and 7th column x1 = test1(1,m).name.data(:,1); pick1 = test1(1,m).name.data(:,17); 213 place1 = test1(1,m).name.data(:,18); Sound = test1(1,m).name.data(:,16); j = 0; t = test1(1,m).name.data(:,1); % for i = 1:length(t) % Sound(i,1) = abs(Sound(i,1) - (0.004753)); % end n1 = 1; % Order wn = 1/(0.5*120); % Cut-off frequency [b,c] = butter(n1,wn,'low'); % Low-pass Butterworth Filter pick= filtfilt(b,c,pick1); place= filtfilt(b,c,place1); i = 1; q = 0; t0 = 0; t1 = 0; t2 = 0; t3 = 0; t4 = 0; t5 = 0; t6 = 0; t7 = 0; t8 = 0; t9 = 0; t10 = 0; t11 = 0; t12 = 0; t13 = 0; t14 = 0; t15 = 0; t16 = 0; t17 = 0; while (i<=length(pick)-500) % if pick(i) >= length(pick) % i = length(pick); % end if (pick(i)-pick(i+10))>= 0.15

if q == 0; if pick(i) >= 3.25 if ((i+650)<=length(pick)) t0 = i; [row,colum1] = (max(place(i:i+360))); t1 = i+colum1;

q = 1; i = i +250; else t0 = 0;t1 = 0; q = 1; end 214

end end

if q == 1; if pick(i) >= 3.25 if ((i+500)<=length(pick)) t2 = i; [row,colum2] = (max(place(i:i+360))); t3 = i+colum2; q = 2; i = i +250; else t2 = 0;t3 = 0;q = 2; end end end

if q == 2; if pick(i) >= 3.25 if ((i+500)<=length(pick)) t4 = i; [row,colum3] = (max(place(i:i+360))); t5 = i+colum3; q = 3; i = i +250; else t4 = 0;t5 = 0;q = 3; end end end

if q == 3; if pick(i) >= 3.25 if ((i+500)<=length(pick)) t6 = i; [row,colum4] = (max(place(i:i+450))); t7 = i+colum4; q = 4; i = i +250; else t6 = 0;t7 = 0;q = 4; end end end

if q == 4; if pick(i) >= 3.25 if ((i+500)<=length(pick)) t8 = i; [row,colum5] = (max(place(i:i+360))); t9 = i+colum5; q = 5; i = i +250; else t8 = 0;t9 = 0;q = 5; end end 215

end

if q == 5; if pick(i) >= 3.25 if ((i+500)<=length(pick)) t10 = i; [row,colum6] = (max(place(i:i+360))); t11 = i+colum6; q = 6; i = i +250; else t11 = 0;t10 = 0;q = 6; end end end

if q == 6; if pick(i) >= 3.25 if ((i+500)<=length(pick)) t12 = i; [row,colum7] = (max(place(i:i+360))); t13 = i+colum7; q = 7; i = i +250; else t12 = 0;t13 = 0;q = 7; end end end

if q == 7; if pick(i) >= 3.25 if ((i+500)<=length(pick)) t14 = i; [row,colum8] = (max(place(i:i+360))); t15 = i+colum8; q = 8; i = i +250; else t14 = 0;t15 = 0; q = 8; end end end

if q == 8; if pick(i) >= 3.25 if ((i+500)<=length(pick)) t16 = i; [row,colum9] = (max(place(i:i+360))); t17 = i+colum9; q = 9; i = i +250; else t16 = 0;t17 = 0;q = 9;

end end 216

end

if (t1 == 0 & t0>0) == 1 t0 = 0; end

if (t3 == 0 & t2>0) == 1 t2 = 0; end

if (t5 == 0 & t4>0) == 1 t4 = 0; end

if (t7 == 0 & t6>0) == 1 t6 = 0; end

if (t9 == 0 & t8>0) == 1 t8 = 0; end

if (t11 == 0 & t10>0) == 1 t10 = 0; end

if (t13 == 0 & t12>0) == 1 t12 = 0; end if (t15 == 0 & t14>0) == 1 t14 = 0;

end

if (t17 == 0 & t16>0) == 1 t16 = 0; end end i = i +1; if q == 9; i = length(pick)-499; end

end

fprintf(MARK,'%15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t%15.4E \t %15.4E \t %15.4E \t

217

%15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \n', m, t0,t1,t2,t3,t4,t5,t6,t7,t8,t9,t10,t11,t12,t13,t14,t15,t16,t17);

% end;

% for n=1:length(t)

% m10 = t9; Flex = zeros; Rot = zeros; Side = zeros; FlBM =zeros; TwM = zeros; SiBM = zeros; FlBV = zeros; TwV = zeros; SiBV = zeros; FlBA = zeros; TwA = zeros; SiBA = zeros; % Fa = zeros; % Fb = zeros; time = zeros;

% temp = t0-50; % if (temp <= 0); % t0 = mark(2); % t1 = mark(3); % t2 = mark(4); % t3 = mark(5); % t4 = mark(6); % t5 = mark(7); % t6 = mark(8); % t7 = mark(9); % t8 = mark(10); % temp = t0-50; % end % temp = t0-30; if t0 > 0; Flex(1) = abs(max(Lum_Flex(t0:t1))); Rot(1) = abs(max(Lum_Rot(t0:t1))); Side(1) = abs(max(Lum_R_Flex(t0:t1))); FlBM(1) = abs(max(FBM(t0:t1))); TwM(1) = abs(max(TM(t0:t1))); SiBM(1) = abs(max(SBM(t0:t1))); FlBV(1) = abs(max(FBV(t0:t1))); TwV(1) = abs(max(TV(t0:t1))); SiBV(1) = abs(max(SBV(t0:t1))); FlBA(1) = abs(max(FBA(t0:t1))); TwA(1) = abs(max(TA(t0:t1))); SiBA(1) = abs(max(SBA(t0:t1))); % Fa(1) = abs(max(fa(t0:t1))); 218

% Fb(1) = abs(max(fb(t0:t1))); time(1) = (t1-t0);

FlexN(1) = (min(Lum_Flex(t0:t1))); RotN(1) = (min(Lum_Rot(t0:t1))); SideN(1) = (min(Lum_R_Flex(t0:t1))); FlBMN(1) = abs(min(FBM(t0:t1))); TwMN(1) = abs(min(TM(t0:t1))); SiBMN(1) = abs(min(SBM(t0:t1))); FlBVN(1) = abs(min(FBV(t0:t1))); TwVN(1) = abs(min(TV(t0:t1))); SiBVN(1) = abs(min(SBV(t0:t1))); FlBAN(1) = abs(min(FBA(t0:t1))); TwAN(1) = abs(min(TA(t0:t1))); SiBAN(1) = abs(min(SBA(t0:t1))); % FaN(1) = abs(min(fa(t0:t1))); % FbN(1) = abs(min(fb(t0:t1))); elseif t0 == 0 Flex(1) = 0;

end if t2 > 0; % temp = t1-30; Flex(2) = abs(max(Lum_Flex(t2:t3))); Rot(2) = abs(max(Lum_Rot(t2:t3))); Side(2) = abs(max(Lum_R_Flex(t2:t3))); FlBM(2)= abs(max(FBM(t2:t3))); TwM(2) = abs(max(TM(t2:t3))); SiBM(2) = abs(max(SBM(t2:t3))); FlBV(2) = abs(max(FBV(t2:t3))); TwV(2) = abs(max(TV(t2:t3))); SiBV(2)= abs(max(SBV(t2:t3))); FlBA(2) = abs(max(FBA(t2:t3))); TwA(2) = abs(max(TA(t2:t3))); SiBA(2)= abs(max(SBA(t2:t3))); % Fa(2) = abs(max(fa(t2:t3))); % Fb(2) = abs(max(fb(t2:t3))); time(2) = (t3-t2);

FlexN(2) = (min(Lum_Flex(t2:t3))); RotN(2) = (min(Lum_Rot(t2:t3))); SideN(2) = (min(Lum_R_Flex(t2:t3))); FlBMN(2)= abs(min(FBM(t2:t3))); TwMN(2) = abs(min(TM(t2:t3))); SiBMN(2) = abs(min(SBM(t2:t3))); FlBVN(2) = abs(min(FBV(t2:t3))); TwVN(2) = abs(min(TV(t2:t3))); SiBVN(2)= abs(min(SBV(t2:t3))); FlBAN(2) = abs(min(FBA(t2:t3))); TwAN(2) = abs(min(TA(t2:t3))); SiBAN(2)= abs(min(SBA(t2:t3))); % FaN(2) = abs(min(fa(t2:t3))); % FbN(2) = abs(min(fb(t2:t3))); 219

elseif t2 == 0 Flex(2) = 0;

end

if t4 > 0; % temp = t2-30; Flex(3) = abs(max(Lum_Flex(t4:t5))); Rot(3) = abs(max(Lum_Rot(t4:t5))); Side(3) = abs(max(Lum_R_Flex(t4:t5))); FlBM(3) = abs(max(FBM(t4:t5))); TwM(3) = abs(max(TM(t4:t5))); SiBM(3) = abs(max(SBM(t4:t5))); FlBV(3) = abs(max(FBV(t4:t5))); TwV(3) = abs(max(TV(t4:t5))); SiBV(3)= abs(max(SBV(t4:t5))); FlBA(3) = abs(max(FBA(t4:t5))); TwA(3) = abs(max(TA(t4:t5))); SiBA(3)= abs(max(SBA(t4:t5))); % Fa(3) = abs(max(fa(t4:t5))); % Fb(3) = abs(max(fb(t4:t5))); time(3) = (t5-t4);

FlexN(3) = (min(Lum_Flex(t4:t5))); RotN(3) = (min(Lum_Rot(t4:t5))); SideN(3) = (min(Lum_R_Flex(t4:t5))); FlBMN(3) = abs(min(FBM(t4:t5))); TwMN(3) = abs(min(TM(t4:t5))); SiBMN(3) = abs(min(SBM(t4:t5))); FlBVN(3) = abs(min(FBV(t4:t5))); TwVN(3) = abs(min(TV(t4:t5))); SiBVN(3)= abs(min(SBV(t4:t5))); FlBAN(3) = abs(min(FBA(t4:t5))); TwAN(3) = abs(min(TA(t4:t5))); SiBAN(3)= abs(min(SBA(t4:t5))); % FaN(3) = abs(min(fa(t4:t5))); % FbN(3) = abs(min(fb(t4:t5)));

elseif t4 == 0 Flex(3) = 0; end

if t6>0; % temp = t3-30; Flex(4) = abs(max(Lum_Flex(t6:t7))); Rot(4) = abs(max(Lum_Rot(t6:t7))); Side(4) = abs(max(Lum_R_Flex(t6:t7))); FlBM(4) = abs(max(FBM(t6:t7))); TwM(4) = abs(max(TM(t6:t7))); SiBM(4) = abs(max(SBM(t6:t7))); FlBV(4) = abs(max(FBV(t6:t7)));

220

TwV(4) = abs(max(TV(t6:t7))); SiBV(4)= abs(max(SBV(t6:t7))); FlBA(4) = abs(max(FBA(t6:t7))); TwA(4) = abs(max(TA(t6:t7))); SiBA(4)= abs(max(SBA(t6:t7))); % Fa(4) = abs(max(fa(t6:t7))); % Fb(4) = abs(max(fb(t6:t7))); time(4) = (t7-t6);

FlexN(4) = (min(Lum_Flex(t6:t7))); RotN(4) = (min(Lum_Rot(t6:t7))); SideN(4) = (min(Lum_R_Flex(t6:t7))); FlBMN(4) = abs(min(FBM(t6:t7))); TwMN(4) = abs(min(TM(t6:t7))); SiBMN(4) = abs(min(SBM(t6:t7))); FlBVN(4) = abs(min(FBV(t6:t7))); TwVN(4) = abs(min(TV(t6:t7))); SiBVN(4)= abs(min(SBV(t6:t7))); FlBAN(4) = abs(min(FBA(t6:t7))); TwAN(4) = abs(min(TA(t6:t7))); SiBAN(4)= abs(min(SBA(t6:t7))); % FaN(4) = abs(min(fa(t6:t7))); % FbN(4) = abs(min(fb(t6:t7))); elseif t6 == 0 Flex(4) = 0; end % temp = t4-30;

if t8>0; Flex(5) = abs(max(Lum_Flex(t8:t9))); Rot(5) = abs(max(Lum_Rot(t8:t9))); Side(5) = abs(max(Lum_R_Flex(t8:t9))); FlBM(5) = abs(max(FBM(t8:t9))); TwM(5) = abs(max(TM(t8:t9))); SiBM(5) = abs(max(SBM(t8:t9))); FlBV(5) = abs(max(FBV(t8:t9))); TwV(5) = abs(max(TV(t8:t9))); SiBV(5)= abs(max(SBV(t8:t9))); FlBA(5) = abs(max(FBA(t8:t9))); TwA(5) = abs(max(TA(t8:t9))); SiBA(5)= abs(max(SBA(t8:t9))); % Fa(5) = abs(max(fa(t8:t9))); % Fb(5) = abs(max(fb(t8:t9))); time(5) = (t9-t8);

FlexN(5) = (min(Lum_Flex(t8:t9))); RotN(5) = (min(Lum_Rot(t8:t9))); SideN(5) = (min(Lum_R_Flex(t8:t9))); FlBMN(5) = abs(min(FBM(t8:t9))); TwMN(5) = abs(min(TM(t8:t9))); SiBMN(5) = abs(min(SBM(t8:t9))); 221

FlBVN(5) = abs(min(FBV(t8:t9))); TwVN(5) = abs(min(TV(t8:t9))); SiBVN(5)= abs(min(SBV(t8:t9))); FlBAN(5) = abs(min(FBA(t8:t9))); TwAN(5) = abs(min(TA(t8:t9))); SiBAN(5)= abs(min(SBA(t8:t9))); % FaN(5) = abs(min(fa(t8:t9))); % FbN(5) = abs(min(fb(t8:t9)));

elseif t8 == 0 Flex(5) = 0; end

if (t10 > 0); % temp = t5-30; Flex(6) = abs(max(Lum_Flex(t10:t11))); Rot(6) = abs(max(Lum_Rot(t10:t11))); Side(6) = abs(max(Lum_R_Flex(t10:t11))); FlBM(6) = abs(max(FBM(t10:t11))); TwM(6) = abs(max(TM(t10:t11))); SiBM(6) = abs(max(SBM(t10:t11))); FlBV(6) = abs(max(FBV(t10:t11))); TwV(6) = abs(max(TV(t10:t11))); SiBV(6)= abs(max(SBV(t10:t11))); FlBA(6) = abs(max(FBA(t10:t11))); TwA(6) = abs(max(TA(t10:t11))); SiBA(6)= abs(max(SBA(t10:t11))); % Fa(6) = abs(max(fa(t10:t11))); % Fb(6) = abs(max(fb(t10:t11))); time(6) = (t11-t10);

FlexN(6) = (min(Lum_Flex(t10:t11))); RotN(6) = (min(Lum_Rot(t10:t11))); SideN(6) = (min(Lum_R_Flex(t10:t11))); FlBMN(6) = abs(min(FBM(t10:t11))); TwMN(6) = abs(min(TM(t10:t11))); SiBMN(6) = abs(min(SBM(t10:t11))); FlBVN(6) = abs(min(FBV(t10:t11))); TwVN(6) = abs(min(TV(t10:t11))); SiBVN(6)= abs(min(SBV(t10:t11))); FlBAN(6) = abs(min(FBA(t10:t11))); TwAN(6) = abs(min(TA(t10:t11))); SiBAN(6)= abs(min(SBA(t10:t11))); % FaN(6) = abs(min(fa(t10:t11))); % FbN(6) = abs(min(fb(t10:t11))); elseif t10 == 0 Flex(6) = 0; end

if (t12 > 0); % temp = t6-30; Flex(7) = abs(max(Lum_Flex(t12:t13))); Rot(7) = abs(max(Lum_Rot(t12:t13))); 222

Side(7) = abs(max(Lum_R_Flex(t12:t13))); FlBM(7) = abs(max(FBM(t12:t13))); TwM(7) = abs(max(TM(t12:t13))); SiBM(7) = abs(max(SBM(t12:t13))); FlBV(7) = abs(max(FBV(t12:t13))); TwV(7) = abs(max(TV(t12:t13))); SiBV(7)= abs(max(SBV(t12:t13))); FlBA(7) = abs(max(FBA(t12:t13))); TwA(7) = abs(max(TA(t12:t13))); SiBA(7)= abs(max(SBA(t12:t13))); % Fa(7) = abs(max(fa(t12:t13))); % Fb(7) = abs(max(fb(t12:t13))); time(7) = (t13-t12);

FlexN(7) = (min(Lum_Flex(t12:t13))); RotN(7) = (min(Lum_Rot(t12:t13))); SideN(7) = (min(Lum_R_Flex(t12:t13))); FlBMN(7) = abs(min(FBM(t12:t13))); TwMN(7) = abs(min(TM(t12:t13))); SiBMN(7) = abs(min(SBM(t12:t13))); FlBVN(7) = abs(min(FBV(t12:t13))); TwVN(7) = abs(min(TV(t12:t13))); SiBVN(7)= abs(min(SBV(t12:t13))); FlBAN(7) = abs(min(FBA(t12:t13))); TwAN(7) = abs(min(TA(t12:t13))); SiBAN(7)= abs(min(SBA(t12:t13))); % FaN(7) = abs(min(fa(t12:t13))); % FbN(7) = abs(min(fb(t12:t13))); elseif t12 == 0 Flex(7) = 0; end

if (t14 > 0); % temp = t7-30; Flex(8) = abs(max(Lum_Flex(t14:t15))); Rot(8) = abs(max(Lum_Rot(t14:t15))); Side(8) = abs(max(Lum_R_Flex(t14:t15))); FlBM(8) = abs(max(FBM(t14:t15))); TwM(8) = abs(max(TM(t14:t15))); SiBM(8) = abs(max(SBM(t14:t15))); FlBV(8) = abs(max(FBV(t14:t15))); TwV(8) = abs(max(TV(t14:t15))); SiBV(8)= abs(max(SBV(t14:t15))); FlBA(8) = abs(max(FBA(t14:t15))); TwA(8) = abs(max(TA(t14:t15))); SiBA(8)= abs(max(SBA(t14:t15))); % Fa(8) = abs(max(fa(t14:t15))); % Fb(8) = abs(max(fb(t14:t15))); time(8) = (t15-t14);

FlexN(8) = (min(Lum_Flex(t14:t15))); RotN(8) = (min(Lum_Rot(t14:t15))); SideN(8) = (min(Lum_R_Flex(t14:t15))); 223

FlBMN(8) = abs(min(FBM(t14:t15))); TwMN(8) = abs(min(TM(t14:t15))); SiBMN(8) = abs(min(SBM(t14:t15))); FlBVN(8) = abs(min(FBV(t14:t15))); TwVN(8) = abs(min(TV(t14:t15))); SiBVN(8)= abs(min(SBV(t14:t15))); FlBAN(8) = abs(min(FBA(t14:t15))); TwAN(8) = abs(min(TA(t14:t15))); SiBAN(8)= abs(min(SBA(t14:t15))); % FaN(8) = abs(min(fa(t14:t15))); % FbN(8) = abs(min(fb(t14:t15))); elseif t14 == 0 Flex(8) = 0; end

if (t16 > 0); % temp = t8-30; Flex(9) = abs(max(Lum_Flex(t16:t17))); Rot(9) = abs(max(Lum_Rot(t16:t17))); Side(9) = abs(max(Lum_R_Flex(t16:t17))); FlBM(9) = abs(max(FBM(t16:t17))); TwM(9) = abs(max(TM(t16:t17))); SiBM(9) = abs(max(SBM(t16:t17))); FlBV(9) = abs(max(FBV(t16:t17))); TwV(9) = abs(max(TV(t16:t17))); SiBV(9)= abs(max(SBV(t16:t17))); FlBA(9) = abs(max(FBA(t16:t17))); TwA(9) = abs(max(TA(t16:t17))); SiBA(9)= abs(max(SBA(t16:t17))); % Fa(9) = abs(max(fa(t16:t17))); % Fb(9) = abs(max(fb(t16:t17))); time(9) = (t17-t16);

FlexN(9) = (min(Lum_Flex(t16:t17))); RotN(9) = (min(Lum_Rot(t16:t17))); SideN(9) = (min(Lum_R_Flex(t16:t17))); FlBMN(9) = abs(min(FBM(t16:t17))); TwMN(9) = abs(min(TM(t16:t17))); SiBMN(9) = abs(min(SBM(t16:t17))); FlBVN(9) = abs(min(FBV(t16:t17))); TwVN(9) = abs(min(TV(t16:t17))); SiBVN(9)= abs(min(SBV(t16:t17))); FlBAN(9) = abs(min(FBA(t16:t17))); TwAN(9) = abs(min(TA(t16:t17))); SiBAN(9)= abs(min(SBA(t16:t17))); % FaN(9) = abs(min(fa(t16:t17))); % FbN(9) = abs(min(fb(t16:t17))); elseif t16 == 0 Flex(8) = 0; end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 224 for k = 1:1:length(time) % fprintf(LOUT, '%15.4E \t %15.4E', subject_id, 24); fprintf(LOUT,'%15.4E \t %s \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t%15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \t %15.4E \n', m, files(m).name, Flex(k),FlexN(k), Rot(k), Side(k),SideN(k), FlBM(k), TwM(k), TwMN(k), SiBM(k) ,FlBVN(k), TwV(k), TwVN(k), SiBV(k), SiBVN(k), time(k));

% fprintf(LOUT,'%15.4E \t %s \t %15.4E \t %15.4E \t %15.4E \n', m, files(m).name, Rot(k), SiBM(k), time(k)); %fprintf(LOUT, '%15.4E \n',files(18).name); end % end; %fclose(LOUT); end;

225