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The Pennsylvania State University

The Graduate School

Harold and Inge Marcus Department of Industrial and Manufacturing Engineering

DESIGN AND ASSESSMENT OF ERGONOMICS OF HAND TOOLS BASED ON

GENDER-SPECIFIC OPERATING STRATEGY: TWO CASE STUDIES ON SHOVELS

AND PRUNING SHEARS

A Dissertation in

Industrial Engineering

Jesun Hwang

Submitted in Partial Fulfillment of the Requirements for the Degree of

Doctor of Philosophy

August 2011

The thesis of Jesun Hwang was reviewed and approved* by the following:

Andris Freivalds Professor of Industrial and Manufacturing Engineering Dissertation Advisor Chair of Committee

Gul E. Okudan Kremer Associate Professor of Engineering Design Program Associate Professor of Industrial and Manufacturing Engineering

Matthew B. Parkinson Assistant Professor of Engineering Design Program Assistant Professor of Mechanical Engineering Affiliate Professor of Industrial and Manufacturing Engineering

Dennis J. Murphy Distinguished Professor of Agricultural Engineering

M. Jeya Chandra Professor of Industrial and Manufacturing Engineering Professor in Charge of Academic Programs & Graduate Program Coordinator

*Signatures are on file in the Graduate School

iii ABSTRACT

In spite of increased automation, there are continuous needs for muscular power and manual hand tools of all sizes in modern farming, gardening, and horticulture. These manual types of hand tools, such as cutting tools, weeders, and cultivators require considerable muscle forces, stressful working postures and repetitive movements. The musculoskeletal load on a person performing manual work with hand-powered hand tools often may result in muscle fatigue and reduced capacity for work in the short-term. In the long-term, the consequences can be cumulative and result in musculoskeletal disorders (MSDs) and chronic muscle pain. The effects can be more severe, if the work is performed by workers who have smaller body size and lesser muscle strength. This trend can be more pronounced in women than in men. Also, it may make men and women take different tool operating strategies although they perform same tasks.

This study investigates the biomechanical and physiological loads when working with shovels in Case Study 1 and with pruning shears of varying design in Case Study 2. The objective of this study was to find usability issues on conventional shovels and pruning shears and integrate ergonomics into the design process to improve users’ safety and health as well as performance.

Special emphasis is placed on the user preference and gender-specific operating strategy. For the study of shovel design, the effects of lift angle, second handle addition, handgrip, preferred handle height selected using a biomechanically recommended position, blade shape, task type, and variations in operator anthropometry are investigated while shoveling. For the study of pruning shear design, the effects of handle shape, gender, hand size, and relationships between hand anthropometric measures and grip force are studied while pruning.

The results of Case Study 1 show that

(1) the redesigned shovel with key ergonomic design parameters (the combination of 36° lift

angle, use of second handle, and elongated D handle) enables the user to perform the

iv shoveling task with less energy as well as a more upright posture while shoveling and

lifting soil.

(2) the design process, considering user preference in handle height selection that improves

accommodation of women users, compared with the design based on solely on

anthropometry.

(3) including a women user preference on the handle height (1145 mm), is capable of

accommodating a larger women population than traditional anthropometric methods, for

the prototype shovel.

(4) knee flexion with a flat back is an operating strategy for women to overcome their

biomechanical disadvantages during shoveling work.

The results of Case Study 2 indicate that

(1) the most critical hand anthropometric measures are hand length and palm width and they

have significant effects on grip span, contact force, and subjective discomfort and

satisfaction rating.

(2) the redesigned pruning shears with rubber-padded grip and thumb grip minimize

pressures on the critical hand regions and significantly improve muscle activities, grip

force distribution, and wrist deviations.

(3) a large degree of wrist extension, greater use of the extensor digitorum (ED) muscle, and

excessive squeezing force are women’s operating strategies to overcome their

biomechanical disadvantages during pruning work.

These results suggest that knowledge of the stress-strain analysis and manual hand tool evaluation for different genders and body sizes will make a significant contribution towards reducing the risk of cumulative trauma disorders (CTD) in the upper extremities of hand tool users.

v TABLE OF CONTENTS

LIST OF FIGURES ...... viii

LIST OF TABLES ...... xii

ACKNOWLEDGEMENTS ...... xiv

Chapter 1: INTRODUCTION ...... 1

1.1. PROBLEM STATEMENT ...... 1

1.2 RESEARCH OBJECTIVES ...... 2

Objective 1 ...... 2

Objective 2 ...... 2

Objective 3 ...... 3

Objective 4 ...... 3

Chapter 2: LITERATURE REVIEW ...... 4

2.1. ERGONOMICS OF HAND TOOLS ...... 4

2.1.1. Ergonomic Design of Hand Tools ...... 4

2.1.2. Ergonomic Design Criteria for Hand Tools ...... 5

2.1.3. Grip Strength, Grip Span, and Wrist Postion ...... 13

2.1.4. Ergonomics of Shovel Design ...... 15

2.1.5. Ergonomics of Pruning Shear Design ...... 16

2.2. ERGONOMICS OF GARDENING ...... 17

2.2.1. Task Components and Risks Associated with Gardening ...... 17

2.3. MUSCLE ACTIVITY ...... 19

2.3.1. The Role of Oxygen in Muscle Actions ...... 19

2.3.2. Physical Work Assessment by Heart Rate ...... 21

vi 2.3.3. Physical Work Assessment by Subjective Rating of Perceived Effort ...... 21

2.4. WORK-RELATED MUSCULOSKELETAL DISORDERS ...... 22

2.4.1. Risk Factors associated with WMSDs ...... 23

2.5. HAND ANATOMY & MECHNISM ...... 27

2.5.1. Ligament and Other Structures ...... 27

2.5.2. Extrinsic Muscles ...... 31

2.5.3. The Effect of Finger Extensor Mechanism ...... 32

2.5.4. Interaction of Wrist and Hand Motion ...... 33

2.5.5. Power Grip ...... 36

Chapter 3: CASE STUDY - SHOVELS ...... 42

3.1. INTRODUCTION ...... 42

3.2. METHODS: PHASE I – DETERMINATION OF KEY DESIGN PARAMETERS ...... 45

3.2.1. Participants ...... 45

3.2.2. Shovel Designs ...... 45

3.2.3. Experimental Design ...... 49

3.2.4. Experimental Procedures ...... 50

3.2.5. Measurements ...... 51

3.3. RESULTS ...... 54

3.4. DISCUSSION AND CONCLUSIONS ...... 57

3.5. METHODS: PHASE II – EVALUATION OF NEW PROTOTYPE OF SHOVEL ... 58

3.5.1. Determination of Optimal Handle Height Including User Preference For New Prototype Shovel ...... 58

3.5.2. Participants ...... 65

3.5.3. Experimental Design ...... 66

3.5.4. Experimental Procedures ...... 68

vii 3.5.5. Results ...... 69

3.5.6. DISCUSSION AND CONCLUSIONS ...... 77

Chapter 4: CASE STUDY – PRUNING SHEARS ...... 80

4.1. INTRODUCTION ...... 80

4.2. METHODS ...... 83

4.2.1. Participants ...... 83

4.2.2. Anthropometric Measurements ...... 83

4.2.3. Experimental Design ...... 86

4.2.4. Experimental Procedures ...... 88

4.2.5. Instrumentation and Apparatus ...... 90

4.3. RESULTS ...... 92

4.3.1. Analysis of Anthropometric Variables ...... 92

4.3.2. Maximum Grip Strength and Anthropometric Variables ...... 93

4.3.3. Grip Force and Contact Force ...... 98

4.3.4. Subjective Ratings ...... 99

4.3.5. Muscle Activity ...... 107

4.3.6. Grip Force Distribution ...... 111

4.3.7. Wrist Deviations in F/E and U/R ...... 118

4.4. DISCUSSION ...... 120

Chapter 5: CONCLUSIONS ...... 127

REFERENCES ...... 131

viii

LIST OF FIGURES

Figure 2-1: Handle size for a cylindrical tool. Both distal interphalangeal (DIP) and proximal interphalangeal (PIP) joints should be in mid-flexion...... 7

Figure 2-2: Handle size for a two- handled tool. Proximal interphalangeal (PIP) joints should be in mid-flexion at the application of force...... 7

Figure 2-3: Overly wide handle openings. Excessive strain is placed on the collateral ligaments of the thumb carpometacarpal (CMC) and metacarpophalangeal (MCP) joints when handle openings are too wide. Force is applied at the DIP joints rather than the PIP joint in this posture (Sanders, 2004)...... 8

Figure 2-4: Loop design scissors distribute pressure evenly across the thenar eminence and fingers (Sanders, 2004)...... 10

Figure 2-5: Handle length. (A) A short handle may injure superficial structures in the thenar eminence, such as the median nerve. (B) Handles should extend proximally through the thenar eminence to avoid contact forces and distribute the pressure through the palm (Sanders, 2004)...... 12

Figure 2-6: Scheme of the relationships between oxygen uptake and heart rate (Lehto and Buck, 2008) ...... 22

Figure 2-7: Joints and bones of the fingers and thumb. Note that each finger has a DIP and PIP joint, whereas the thumb only has an IP joints (Lippert, 2006)...... 27

Figure 2-8: The flexor retinaculum is made up of the palmar and transverse carpal ligaments (Lippert, 2006)...... 28

Figure 2-9: The bony floor of the carpal bones and fibrous ceiling of the transverse carpal ligament form the carpal tunnel. The median nerve and several tendons pass through this tunnel. Note the area of the hand innervated by this nerve (Lippert, 2006)...... 29

Figure 2-10: Extensor retinaculum (Lippert, 2006)...... 30

Figure 2-11: The extensor expansion provides an attachment on the middle and/or distal phalanx for several muscles (Lippert, 2006)...... 30

Figure 2-12: The three arches of the hand (Lippert, 2006)...... 31

Figure 2-13: Flexor digitorum superficialis (left) and Extensor digitorum (right) (Lippert, 2006)...... 32

Figure 2-14: A schematic illustration of lateral view of the extensor mechanism...... 33

ix Figure 2-15: Role of wrist position in finger function...... 34

Figure 2-16: When the wrist is flexed, the tip of the thumb is level with the distal interphalangeal joint of the index finger. With the wrist in extension, the pulps of the thumb and index finger come passively into contact (Tubiana, 1984)...... 35

Figure 2-17: The two fundamental patterns of prehensile hand function...... 37

Figure 3-1: 3D lifting posture simulation for the participants from Penn State Women Agricultural Society...... 46

Figure 3-2: Configurations for commercial shovel and common terms for shovel components...... 48

Figure 3-3: Configurations for new prototype shovels...... 48

Figure 3-4: Second handle attachment...... 49

Figure 3-5: Shovel handgrip conditions. Normal (left). Elongated D (middle). Contoured D (right)...... 50

Figure 3-6: Shoveling simulated laboratory setting...... 51

Figure 3-7: S147 rapid response O2/CO2 analyzer (Qubit Systems Inc.)...... 52

Figure 3-8: S182 wireless heart rate monitor (Qubit Systems Inc.)...... 52

Figure 3-9: Projected posture estimation on a 2 by 2 mm grid...... 54

Figure 3-10: Method to determine preferred handle height and its relevant anthropometric measurements...... 59

Figure 3-11: Preferred handle height plotted against stature and trochanterion for the 9- women participant sample, with regression line...... 61

Figure 3-12: Distributions of 1000 random stature values in the NHANESWOMEN...... 62

Figure 3-13: Stature, trochanteric height, and preferred handle height estimated for NHANESWOMEN with including preference...... 64

Figure 3-14: Bi-functional round-point-gooseneck long socket blade...... 67

Figure 3-15: Position for the second handle attachment by the first-class level system...... 68

Figure 3-16: Interaction plot (data means) for Perceived Discomfort...... 73

Figure 3-17: Interaction plot (data means) for Perceived Exertion...... 74

Figure 3-18: Interaction plot (data means) for Perceived Fatigue...... 75

x Figure 3-19: Interaction plot (data means) for Shoveling Performance...... 75

Figure 3-20: Interaction plot (data means) for Oxygen Consumption (VO2)...... 76

Figure 3-21: Interaction plot (data means) for Normalized Heart Rate...... 76

Figure 3-22: Lifting strategy by men and women...... 78

Figure 3-23: Schematic diagram of moment arms and forces acting on L5/S1 while lifting (left). Lifting strategies differentiated by gender (right)...... 79

Figure 3-24: 3D simulation results of observed women lifting strategy in Phase II...... 79

Figure 3-25: 3D simulation results of observed men lifting strategy in Phase II...... 79

Figure 4-1: Visual description of hand measurements...... 84

Figure 4-2: Position of the upper handle during actual usage...... 85

Figure 4-3: Hand-powered pruning shear designs...... 86

Figure 4-4: Localized force on the palm side aligned with the thumb finger...... 87

Figure 4-5: Thumb finger remaining passively during operating the pruning shear...... 87

Figure 4-6: Schematic view of the thumb grip attachment...... 88

Figure 4-7: The Jamar hand dynamometer where each handle is wrapped by force sensing resistors...... 89

Figure 4-8: Pruning simulated workstation...... 90

Figure 4-9: The FlexiForce A101 sensor, has a sensing area of 0.375 in. (9.533 mm) and can measure forces up to 25 lbs...... 91

Figure 4-10: The FlexiForce 1235 OEM trimmable sensor and can measure forces up to 100 lbs...... 91

Figure 4-11: Force glove system and sensor locations...... 91

Figure 4-12: Curve fit for maximum grip strength...... 97

Figure 4-13: Jamar grip strength as a function of contact force by gender...... 99

Figure 4-14: Investigated hand regions for subjective discomfort rating...... 101

Figure 4-15: Subjective discomfort rating on finger region by gender and pruning shear...... 102

xi Figure 4-16: Interaction plot (data means) for subjective discomfort rating on thenar region...... 102

Figure 4-17: Interaction plot (data means) for subjective discomfort rating on wrist region...... 103

Figure 4-18: Interaction plot (data means) for subjective satisfaction of grip force requirement by pruning shear and gender...... 104

Figure 4-19: Average subjective satisfaction of grip force requirement by pruning shear design...... 105

Figure 4-20: Subjective satisfaction of grip span by gender and hand size...... 105

Figure 4-21: Average subjective satisfaction of grip span by hand size...... 106

Figure 4-22: sEMG of the forearm muscles as a function of Pruning Shear...... 108

Figure 4-23: sEMG of FDS and ED by gender...... 109

Figure 4-24: sEMG of FDS and ED by hand size...... 109

Figure 4-25: Interaction plot (data means) for sEMG (FDS) by gender and hand size...... 110

Figure 4-26: Total and individual phalange forces by gender...... 113

Figure 4-27: Total and individual finger forces by gender...... 113

Figure 4-28: Total finger/palm forces by pruning shear design...... 116

Figure 4-29: fpBalance data by pruning shear...... 117

Figure 4-30: Improved fpBalance while operating TGP...... 124

Figure 4-31: Improved fpBalance while operating RGP...... 124

Figure 4-32: An example of sEMG plots with wrist deviation obtained from large hand sized men and small/medium hand-sized women participants...... 126

xii

LIST OF TABLES

Table 2-1: Ergonomic risks associated with gardening and potential solutions (Sanders, 2004)...... 18

Table 3-1: Participant Characteristics (n = 9)...... 45

Table 3-2: Physical characteristics of eighteen shovels...... 47

Table 3-3: Descriptive statistics for the eight shoveling conditions...... 55

Table 3-4: Results of ANOVA to 3*3*2 factorial designs...... 56

Table 3-5: Results of paired t-test: Commercial vs. RedesignedOPT Shovel...... 57

Table 3-6: Summary of nine women anthropometric measurements taken from Phase I. (unit: mm) ...... 60

Table 3-7: Trochanteric height comparison of NHANESWOMEN with ANSUR...... 63

Table 3-8: Preferred handle height, shaft length for selected percentile...... 65

Table 3-9: Participant characteristics (Phase II) ...... 66

Table 3-10: Experimental conditions in Phase II...... 67

Table 3-11: The effect of shovel type on physiological and subjective variables (Commercial vs. RedesignedPHASE(II)) ...... 70

Table 3-12: The effect of shovel type on physiological and subjective variables (Best in Phase I vs. Redesigned shovel) ...... 71

Table 3-13: The effect of gender on the degree of knee flexion at the moment of lifting...... 71

Table 3-14: Results of MANOVA...... 73

Table 3-15: Adjustability ranges from preferred handle height and shaft length for selected percentiles...... 77

Table 4-1: Summary of participant characteristics ...... 85

Table 4-2: Summary statistics for anthropometric variables...... 93

Table 4-3: Summary of maximum grip strength data by gender...... 94

xiii Table 4-4: One-way ANOVA result for maximum grip strength by gender...... 94

Table 4-5: Summary of maximum grip strength data by hand size...... 94

Table 4-6: One-way ANOVA result for maximum grip strength by hand size...... 95

Table 4-7: Bonferroni multiple comparisons for maximum grip strength...... 95

Table 4-8: Pearson’s correlation matrix for maximum grip strength and anthropometric variables...... 96

Table 4-9: Curve estimation regression model summary and parameter estimates...... 97

Table 4-10: Summary of maximum grip strength and total contact force data...... 98

Table 4-11: Curve estimation regression model summary and parameter estimates...... 98

Table 4-12: Results of MNOVA and ANOVA for subjective hand discomfort rating data. Each cell is represented as F-statistic (p-value)...... 101

Table 4-13: Results of MNOVA and ANOVA for subjective design satisfaction rating data. Each cell is represented as F-statistic (p-value)...... 104

Table 4-14: Results of MNOVA and ANOVA for sEMG data for FDS and ED. Each cell is represented as F-statistic (p-value)...... 108

Table 4-15: Summary of total and individual finger/phalange forces by gender...... 112

Table 4-16: One-way ANOVA result for total and individual finger/phalange forces by gender...... 114

Table 4-17: Total and individual finger and phalange force contributions...... 115

Table 4-18: Summary of total finger/palm force and balance by pruning shear design...... 116

Table 4-19: One-way ANOVA result for total finger/palm force and balance by pruning shear design...... 117

Table 4-20: Summary of wrist deviation in F/E and U/R by pruning shear design...... 118

Table 4-21: One-way ANOVA result for wrist deviations in F/E and U/R by pruning shear design...... 119

Table 4-22: Summary of wrist deviations in F/E and U/R by gender...... 119

Table 4-23: One-way ANOVA result for wrist deviations in F/E and U/R by gender...... 120

xiv

ACKNOWLEDGEMENTS

First and above all, I praise God, the almighty, merciful, and passionate, for preparing me to study abroad, providing me this opportunity to step in the excellent world of Human Factors, and granting me the capability to pursue a Ph. D. in Industrial Engineering successfully. The

Bible says, “The fear of the LORD is the beginning of knowledge, but fools despise wisdom and discipline. (Proverbs 1:7).” This word of the Lord is the primary motivation for the pleasure of this study. To be able to step strong and smooth in this way, I have also been supported and supervised by many people to whom I would like to express my deepest gratitude.

Dr. Andris Freivalds, my esteemed advisor, my truly thanks for accepting me as a Ph.D student, your continuous encouragement, insightful discussion, thoughtful guidance, critical comments, and correction of the thesis. I would like to thank the members of Ph.D. committee,

Dr. Gul E. Okudan Kremer, Dr. Matthew B. Parkinson, and Dr. Dennis J. Murphy for their excellent advises and detailed review while completing this thesis. Korean IE students at Penn

State helped and assisted me about research, life, and future.

I do appreciate all of my family members who have tried to be helpful for this thesis and academic life. Especially, my wife and daughter provided more support and encouragement than I could have ever desired for. I am truly inspired by the prayer and love they’ve shown throughout this work. Thank you—Minjae and Grace—for your spiritual support in all aspects of my life.

Jesun Hwang

Chapter 1

INTRODUCTION

1.1. PROBLEM STATEMENT

In a human-work system where hand tools are used to carry out tasks, the tools will have an effect on the amount of force a worker must exert and on working posture, efficiency and the degree of comfort experienced during work. Hand tool ergonomics influences the physical workload. A comprehensive review of studies concerning the effectiveness of ergonomics interventions, including studies on the redesign of hand tools, the modification of hand tool ergonomics and the reduction of force and posture demands, has been compiled (Grand and

Habes, 1995). Earlier principles concerning the use and the design of hand tools have been presented (Freivalds, 1987; Meagher, 1987). Kadefors et al. (1993a) have concentrated on hand tool evaluation and have established a list of factors that should be considered in evaluating the ergonomics of hand tools. Also a study concerning tool design, user characteristics and performance has been published (Kilbom et al., 1993a). For the classification of work with hand tools and the formulation of functional requirements an analysis model has been presented

(Kilbom et al., 1993a; Sperling et al., 1993). Also detailed design instructions for different kinds of hand tools have been compiled by the Eastman Kodak Company (2004), Freivalds (1987),

Lewis and Narayan (1993) and Mital and Kilbom (1992a, 1992b).

Though several studies on hand tool evaluation and design have been published, a comprehensive ergonomic evaluation or assessment of the most important design criteria concerning variations in user anthropometry and preference on the working posture for shovels and pruning shears seems to be lacking. To achieve comprehensive ergonomic interventions for

2 hand tools, the designer should be familiar with the anatomy and functioning of the body and the gender-specific operating strategy that can be caused by biological differences. These differences may place women, who potentially have physiological and biomechanical disadvantage, at risk for work-related musculoskeletal disorders when using traditionally designed tools.

1.2 RESEARCH OBJECTIVES

The design of hand tools can be improved through research on the biomechanics and ergonomics of the human body and user preference. The aim of this study is to (1) find potential problems on existing shovels and pruning shears, (2) design and develop new ergonomic interventions for those problems, and (3) evaluate ergonomics of those hand tools by comparing the redesigned tools with existing tools to verify ergonomically valid design solutions. Detailed objectives are following:

Objective 1

The first objective of the shovel study is to test the hypothesis that the lift angle, addition of a second handle, and type of handgrip would significantly affect on the physiological, kinematic, and performance variables.

Objective 2

The second objective of the shovel study is to determine an optimal handle height by including user preference component and test the effects of shovel type and task type on physiological and subjective variables.

3 Objective 3

The third objective of pruning shear study is to test the hypothesis that the handle design, gender, and hand size would significantly affect on the subjective hand discomfort, subjective design satisfaction, muscle activity, grip force distribution, and wrist deviations.

Objective 4

The fourth objective of this study is to test the hypothesis that the gender would significantly affect on the hand tool operating strategy to overcome biological disadvantages or to adopt biomechanical advantages.

Chapter 2

LITERATURE REVIEW

2.1. ERGONOMICS OF HAND TOOLS

2.1.1. Ergonomic Design of Hand Tools

Hand tools can be considered to be an apparatus that compensate for human inadequacies and limitations while performing manual tasks. These limitations can be related to strength

(pliers, wire cutters, and pruning shears), penetrability (saws, files), bluntness (knives, scissors, and drills), shortness (tongs), flexibility (hammer) or limited speed (hammer handle). (Cacha,

1999) As hand tools are used daily, they have a strong effect on health, product quality, work performance, use of force, local muscular discomfort, biomechanical strain and professional pride in industrial work (Meagher, 1987; Chaffin and Andersson, 1991; Ulin et al., 1995; Kardborn,

1998).

By improving the ergonomics and usability of hand tools, work efficiency, productivity and quality as well as user comfort and safety can be improved (Meagher, 1987; Buchholz et al.,

1992, Kadefors et al., 1993a; Kilbom et al., 1993a; Sperling et al., 1993b; Tudor, 1996; Kardborn,

1998). Ergonomically well-designed hand tools used in work situations with balanced work content reduce the risk of occupational injuries of the hand, wrist and forearm (Sperling et al.,

1993b). Tichauer (1978) reported that improvement of hand tool design could lower the incidence of musculoskeletal disorders. However, it must be noted that Leamon and Dempsey (1995) were strongly critical of the reliability of Tichauers’ report.

Kilbom et al (1993a) demonstrated that by improving the ergonomic quality of hand tools it is possible to increase the productivity of work. This is important also from the viewpoint of

5 workers’ health as they usually use tools with the highest productivity even at the cost of higher degree of a strain and fatigue (Kadefors et al., 1993a; Kilbom et al., 1993a).

Hand tools still cause occupational disorders in many professions and are still involved in many industrial accidents (Cederquist and Lindberg, 1993; Kadefors et al., 1993a). Over the years much effort and research have been devoted to the explanation and understanding of the interrelationship between human performance and hand tool design with the aim to ensure that hand tools are used more effectively, accurately, comfortably and safely (Cederquist and

Lindberg, 1993; Mattila et al., 1993; Rouvali and Mattila, 1993; Kihlberg, 1995; Ulin et al., 1995;

Tudor, 1996; Vilkki et al., 1996; Kardborn, 1998; Päivinen et al., 2000; Nevala-Puranen and

Lintula, 2001; Niemelä and Päivinen, 2001).

2.1.2. Ergonomic Design Criteria for Hand Tools

Today, industry consultants and managers must consider not only the most appropriate tool for the specific job but also the range of tool sizes necessary for a diverse workforce. Most obviously, tools that are balanced and sized for men with larger muscle mass will demand more force from women users with smaller hand mass. Conversely, the operation of precision tools that are balanced and designed for a smaller hand will cause excessive strain for men with larger hand mass. As Meagher (1987) explained, “One size does not fit all.” Tools must be sized to fit the worker, and consideration must be given to the normal biomechanics of the hand. Further, workers should try out the tools before committing to their long-term use. Meagher (1987) suggests that the most important elements of tool design with regard to human usage are handle size, shape, and texture, ease of operation, shock absorption, and weight.

6 Handle Diameter and Span

The handle size refers to either the diameter of the tool handle, for cylindrical tools, or the span between handles, for crimping tools or tools with two handles. The correct tool handle size allows the worker to generate optimal strength for the job without straining the flexor tendons or intrinsic muscles.

Cylindrical Tools. To generate the maximum grip strength, the flexor digitorum superficialis and flexor digitorum profundus provide flexion forces, and the intrinsic muscles stabilize the tool in the hand. When a power grasp is used on a tool with a cylindrical handle, the proximal and distal interphalangeal joints should be in midflexion; the distal joint of the middle and ring fingers should overlap the distal joint (or part of phalange) of the thumb.

The optimal diameter for torque development in a cylindrical tool varies slightly according to type of effort exerted. Axial thrust involves shear forces acting on the cylindrical surface and is best generated with a handle size of 4 cm with ranges from 3 to 5 cm, depending on the individual’s hand size (Cochran and Riley, 1986; Eastman Kodak Company, 2004; Pheasant and Haslegrave, 2006). For tools that are gripped and turned about a perpendicular axis (T- wrench) or straight on (hammer) (Figure 2-1), the optimal grip diameter may be larger (5 to 6 cm) since the force generation is less dependent on the handle size and shape. Grip strength generally increases with diameter up to a certain point and then decreases (Mital and Pennathur, 2001).

Gripping can be enhanced with a thumb stall to reduce slippage (Robinson and Lyon, 1994).

Two-Handled Tools. The span between handles for crimping tools or double-handled tools should be 2.5 to 3.5 inches (6.5 to 9.0 cm) at the application of force (Eastman Kodak

Company, 2004). The maximal flexor force should be leveraged at the proximal interphalangeal joint to use the stronger flexor digitorum superficialis tendons for flexion. Crimping tools should have a spring opening so as not to injure the dorsal structures of the hand against the handle when

7 opening the jaws of the tool. The spring should open the handles no more than 3.5 to 4.5 inches (9 to 11.5 cm) to prevent stretching the thumb collateral ligaments (Figure 2-2).

Figure 2-1: Handle size for a cylindrical tool. Both distal interphalangeal (DIP) and proximal interphalangeal (PIP) joints should be in mid-flexion.

Figure 2-2: Handle size for a two- handled tool. Proximal interphalangeal (PIP) joints should be in mid- flexion at the application of force.

8 Inappropriately Sized Tools. If a tool’s handle diameter is not appropriately sized, the hand muscles and ligaments become strained and easily fatigued when using the tool. For example, if the tool diameter or span between handles is too large, the force is applied at the distal phalanges. The weaker flexor muscle, the flexor digitorum profundus, becomes the primary flexor. When force is applied at the distal phalanx, the tendon force is two to three times greater than when forces are applied at the middle phalanx. Handle openings on crimping tools that are too wide also place excess stress on the collateral ligaments of the thumb carpometacarpal and metacarpophalangeal joints (Figure 2-3). If the handle is too small, the finger flexors and intrinsics must generate more force because the muscles are already contracted maximally and thus are at a mechanical disadvantage. The intrinsics must generate added force to maintain the position (Johnson, 1990).

Handle Contour

The shape or contour of a tool’s handle should follow the transverse arch of the hand to use the stronger ulnar musculature and to permit an even application of force between all fingers.

The handle should rest on the thenar and hypothenar eminences to prohibit compression of the neurovascular bundles between the fingers (Meagher, 1987). Most tool handles are cylindrical in shape, although a slightly curved or cone shape better facilitates gripping by following the transverse arch (Fraser, 1989).

Optimal Shape. Studies regarding the relationship between handle shape and muscle force suggest that the optimal shape for developing torque on a tool relates to the direction of the forces exerted and type of task performed. The area of the grip should be maximized in order to avoid localized pressure. Studies suggest the following (Cochran and Riley, 1986; Mital and

Pennathur, 2001).

Digital Separators. Digital separators or finger recesses present both biomechanical and neurovascular problems. Separators force the fingers into abduction, which strains the intrinsic musculature and flattens the hypothenar eminence. Further, the separators may apply pressure to neurovascular bundles (the digital arteries and nerves) lateral to each finger. Although the separators were originally designed to promote handle control, the separators actually limit a worker’s options or moving or adjusting the tool in his or her hand (Tichauer, 1966; Mital and

Pennathur, 2001; Eastman Kodak Company, 2004).

Finger Rings. Finger rings pose the same problem, as do digital separators in terms of compressing the neurovascular bundles lateral to each finger. The finger loops place pressure on a small surface area and can injure dorsal or volar structures below the loops. Loop-design scissors allow for a more even distribution of pressure in the hand (Figure 2-4).

Figure 2-4: Loop design scissors distribute pressure evenly across the thenar eminence and fingers (Sanders, 2004).

Handle Orientation

A tool handle that is not well oriented to the body causes the worker to assume awkward postures during work tasks and to use more force to accomplish the task. Workers often compensate for wrist deviation by elevating the elbows and abducting the shoulders, thus transferring stresses to another area of the body. Many tools, such as hammers or pliers, necessitate positioning the hand in ulnar deviation to accomplish a task (Robinson and Lyon,

1994).

Tichauer (1978) found a high incidence of tenosynovitis among workers performing wiring operations at an electronics manufacturing plant. When the traditional straight-handled pliers were replaced with bent-handle designs, the incidence of tenosynovitis decreased from 60% to 10% for those using the bent-handle design. The adage “Bend the tool, not the hand” signifies that a neutral wrist position is optimal for tool use. Handle curves are recommended for tools that

11 require the hand to be positioned in ulnar deviation during use, such as hammers, pliers, and saws. For most tools, at least a 20-degree curve positions the hand in neutral and, thus, decreases ulnar deviation (Schoenmarklin and Marras, 1989a; Tichauer, 1966). Novice workers seem to derive more benefit from handle curves than do experienced workers.

Curved handles are most effective when all work is performed on the same plane.

However, the proper handle orientation also depends on the work surface being used. In-line cylindrical tools can be used for drill work being performed on a horizontal surface, such as a workbench, whereas a pistol grip is effective for work performed on a vertical surface.

For pistol grips, the angle of the handle in relation to the longitudinal axis should be 70 to

80 degrees (Robinson and Lyon, 1994; Mital and Pennathur, 2001). Tools such as paint brushes, rollers, hoes, and garden equipment can be adapted with pistol grips (Johnson, 1990).

Handle Length

Sufficient length of a tool is necessary to distribute the pressure of forces evenly across the hand and to prevent direct pressure on the median nerve in the palm of the hand or at the base of the thumb. A tool handle should be long enough to extend proximal to the thenar eminence and permit adequate freedom of movement on the handle (Putz-Anderson, 1988). A short tool handle

(Figure 2-5A) may injure not only the superficial median or ulnar nerves but also the tendon sheaths, causing trigger finger and digital neuritis. Figure 2-5B shows a more even distribution of forces on the thenar eminence structures.

Anthropometric data suggest that the range of palm width is 2.8 to 3.6 inches (Eastman

Kodak Company, 2004). The minimum tool length recommended for most tasks is 4 inches (10 cm), although a length of 5 inches (13 cm) is preferred. When gloves are to be worn during tool use, an additional 0.5 inches (13 mm) should be added to the tool’s length (Putz-Anderson, 1988).

Tool Weight and Balance

In general, tools should weigh as little as possible. Particularly for precision tasks, a lighter tool will require less force to support than will a heavy tool. In some cases, such as power tools, reducing the weight of a tool will require that more force be exerted to operate the tool, and this will increase shoulder tension. The decision regarding whether to increase or decrease the weight of a tool will depend on how that tool is used.

Guidelines suggest that tools weigh no more than 5 pounds (2.3 kg) if the tool must be supported by the hand and arm or if the tool is being operated away from the body. Tools used in precision work should weigh no more than 1 pound (0.4 kg). Tools that are heavier should be counterbalanced with an overhead sling that is positioned perpendicular to the task. Tools should be well balanced to reduce hand fatigue. The center of gravity of the tool should be located close to the handgrip (Armstrong, 1990; Robinson and Lyon, 1994; Eastman Kodak Company, 2004).

13 Tool Position

Operating a tool requires a combined effort of supporting and controlling the tool. Often, the body is forced into awkward positions during one of these two acts because of the position of the task or the tool. As stated previously, the body should be in neutral for the best biomechanical advantage. Shoulders should be positioned at less than 25 to 30 degrees of abduction, and the wrist should be in neutral. Through use of a vice, the worker can maintain neutral wrist and arm positions and leverage body weight. An assortment of vices, jigs, tilted surfaces, and overhead pulley systems and fixtures can aid the worker in improving the tool position and minimizing the weight needed to support the tool or task itself (Armstrong, 1990).

2.1.3. Grip Strength, Grip Span, and Wrist Postion

Pheasant and O’Neill (1975) investigated handle design in a gripping task using a screwdriver. They found that strength deteriorated when handles greater than 5 cm in diameter were used and that, to reduce abrasion of the skin, hand-handle contact should be maximized.

Knurled cylinders were found to be superior to smooth cylinders because of the increase in friction at the hand-handle interface. The authors concluded that, for forceful activities, the size of a handle rather than its shape was most important. A useful rule of thumb for evaluating handle diameters is that the handle should be of such a size that it permits slight overlap of the thumb and fingers of a worker with small hands.

An isometric grip, performed with parallel handles, has been investigated by several studies, e.g., Bechtol (1954), Hertzberg (1955), Montoye and Faulkner (1965), Cotten and

Bonnell (1969), Cotten and Johnson (1971), Petrofsky et al. (1980), Pheasant and Scriven (1983), and Ergonomics Group at Eastman Kodak Company (2004). Most of the studies describe an

14 optimal handle separation, giving maximal force output. This varies between 38 mm and 64 mm depending on gender, equipment and experimental design. A dynamic grip, performed with angulated handles, was studied by Fitzhugh (1973). At a closing speed of 29 mm/s, the highest force was developed when using an initial handle separation of 83-89 mm. Still, the optimal handle separation, where the highest force was obtained, was approximately 52 mm. An isometric grip, performed with angulated handles, is of great interest to cross-action tool work, because many tasks are performed with such a grip.

One of the most important criteria for handle design is provision for sufficient contact between the hand and handle. The larger the handle diameter, the bigger the torque that can be applied to it, in principle, but people with small hands must be able to enclose the handle with their fingers. A handle diameter of 40 mm seems to be the maximum for men users, smaller still if gloves are to be worn. Cylindrical handles are better than handles with finger grooves since these cause pressure ‘hot spot’ and blistering of the skin of hands they do not fit. Handle lengths should be at least 11.5 cm plus clearance for large (95th percentile) hands.

Grip strength depends very largely on the posture of the wrist. When the wrist is extended, the finger flexors are lengthened and can therefore exert more tension resulting in a stronger grip. When the wrist is flexed, the opposite occurs and grip strength is severely weakened. The pronation and flexion of the wrist also shortens and therefore weakens the finger flexor. A general requirement of handle design is that the wrist joints should be kept in a neutral position where the movements are in the middle of their ranges of motions. Pheasant (1986) describes how the axis of a handle is at an angle 100-110 degrees with respect to the forearm when the wrist is in a neutral position.

Plier-like tools can be designed with obliquely set handles to enable the wrist to be maintained in the neutral position (Tichauer, 1978). When using straight-handled tools there is a tendency for the wrist to be deviated to the ulnar direction. This stretches the tendons of the

15 forearm muscles on one side, causing them to rub against a bony protrusion on the thumb side of the wrist, which is know as the radial styloid (Bridger, 2003). Repeated exposure can cause the sheath (synovium) within which the tendon runs to become inflamed (DeQuervain’s syndrome)

(Bridger, 2003). Inflammation of tendons and tendon sheaths can occur in other parts of the hand and other body structures (Bridger, 2003). In the long term, permanent damage to the tendon and its sheath may result. The build-up of scar tissue in the tendon may ultimately reduce the range of movement of the wrist.

2.1.4. Ergonomics of Shovel Design

Digging and shoveling are common tasks in a range of industries including construction, farming and horticulture as well as in leisure pursuits such as gardening. Strictly speaking, digging may be defined as breaking, turning and/or excavating soil and shoveling as transferring loose material from one place to another. In practice, there is considerable overlap between the two since the soil to be dug may be loose or the material to be shoveled may be impacted. All over the world, a large number of people engage in digging and shoveling either frequently or occasionally and both are a form of manual handling using purpose-built hand tools.

Freivalds (1986a, b) reviewed the literature on shoveling and shovel design. At the turn of the century, F. W. Taylor specified an optimal shovel load of 9 kg and pointed out the need for the design of the shovel blade to be matched to the density and consistency of the material to be moved. A shoveling rate of 18-21 scoops per minute has been recommended with a load of 5-11 kg. Shovels should be as light as possible without sacrificing too much strength and consistency.

Sen (1984) reported that shovel design could be improved by fitting a second handle to the neck of the shovel, thereby reducing the need to stoop. Freivalds (1986b) reported that the second handle was more of a hindrance than a help due to usability problems. Neither Freivalds

16 nor Sen reported data to support their claims for or against the alternative design. The rationale for the addition of a second handle appears to be that it enables the user to lift the loaded blade with the hand vertically above the neck of the shovel while reducing the need to stoop. Degani et al (1993) evaluated a novel shovel design with two perpendicular shafts. Lumbar paraspinal EMG activity was significantly less when the two-handled shovel, compared to the conventional shovel, was used. Furthermore, in a field study, subjects had a lower rating of perceived exertion when digging with the levered shovel, compared to the conventional tool. Subjects also reported that less bending was required with the levered shovel.

2.1.5. Ergonomics of Pruning Shear Design

Pruning shears are typically used with one hand and held with a power grip, the palm handle pressing on the line joining the base of the thumb to the hypothenar area while the lower handle is activated by finger flexion (Päivinen, Haapalainen, & Mattila, 2000). Pruning with hand-powered pruning shears increases the risk of musculoskeletal hand–wrist disorders

(Roquelaure, Gabignon, & Gillant, Transient hand paresthesias in vineyard workers of

Champagne, 2001). Roquelaure, Dussolier, & Dano (2002), mainly because of the magnitude of the physical load during the pruning task which requires repetitive handgrips and wrist movements (Roquelaure et al., 2002), combined with static work in the upper arm–shoulder system (Wakula & Landau, 2000). Due to their extensive use, it is essential to improve the ergonomic qualities of hand- powered pruning shears, and new hand-powered pruning shears, characterized by the lateral and vertical inclinations of the blades and a rotating lower handle, have been designed to attempt to reduce physical effort and discomfort during grapevine pruning.

17 2.2. ERGONOMICS OF GARDENING

The motivations for gardening areas varied as gardeners themselves. Gardening offers endless opportunities for problem solving and developing a sense of pride and accomplishment.

Growing and cultivating plants can be aesthetically pleasing to the senses and challenges our creativity and imagination. However, gardening may result in sore and aching muscles, back and hand joint pain, and overexposure to environmental elements (Sanders, 2004).

2.2.1. Task Components and Risks Associated with Gardening

The typical components of gardening include the following.

(1) Digging: Most often using a shovel or spade, digging is required to excavate and prepare

the soil for planting by turning over and breaking up the soil. This task is performed

either prior to or at the beginning of the gardening season, usually in early spring. The

end of the growing season also requires digging to remove dead plants and to prepare the

soil for the next growing season.

(2) Raking: Raking is performed to clear the ground of loose debris and smooth the planting

surface. Most raking occurs during the spring and fall.

(3) Hoeing: The hoe is a multiple-use tool that aids the gardener in creating rows for planting

seeds at a variety of soil depths and in removing weeds throughout the growing season.

(4) Seeding: Adding seeds to a prepared garden bed can be performed by hand or with the

aid of a tool.

(5) Weeding: Management of unwanted plants in the garden can be done by pulling out

weeds by hand or by using a hoe or other tool that digs out the weeds’ root system.

Weeding is performed throughout the growing season as needed.

18 (6) Harvesting: Gathering and reaping the rewards of one’s labor is usually done by hand.

Flowers, herbs, vegetables, and fruits can be picked and collected in a variety of

containers or simply in the hand. Plants mature at different rates and will therefore be

harvested at different times of the season.

Each of the set asks potentially involves biomechanical risk factors that may contribute to or aggravate a musculoskeletal disorder (MSD). Table 2-1outlines the risk factors and potential solutions for the gardening tasks described. When gardening at ground level, most aspects of gardening involve some degree of dynamic trunk and low-back flexion, kneeling, and repetitive grasping of tools or plants. When these postures are assumed for an extended period, strain on the knees, hips and ankles, back, and hands may develop. Raking and soil tilling are both strenuous activities that require substantial upper-body and back strength, as well as good balance to support and use these tools properly. The process of weeding involves high-grip forces in addition to a typically stooped (flexed low back, trunk, and knee) posture.

Table 2-1: Ergonomic risks associated with gardening and potential solutions (Sanders, 2004).

Tasks Biomechanical Risk Factors Solutions Prolonged trunk flexion posture Use extended-handle tools Digging Forceful grasping Dig using feet against shovel instead of using hands Force applied to feet Wear heavy shoes if digging using foot Repetitive flexion and extension of the Take frequent breaks (every 20 minutes) Raking shoulder Trunk flexion Use proper size and type of rake Prolonged kneeling and trunk flexion due to Use a kneeling mat as cushioning for knees. awkward positions or overreaching to plants Take stretch breaks every 20 minutes Hoeing Use ergonomic tools to permit a neutral wrist position Awkward and forceful hand positions and greater leverage Prolonged kneeling and trunk flexion Use a kneeling mat for cushioning Seeding Static posturing Stretch in extended position every 20 minutes Prolonged kneeling and trunk flexion Use a kneeling mat for cushioning and small bench Weeding Forceful hand grasping Use gloves with rubber palms for efficient grasping Harvesting Prolonged trunk and low back flexion Take frequent breaks

19 Although tools enable gardeners to work more efficiently with less force, gardening tools can be heavy and cumbersome for even the most physically fit gardeners when used repetitively.

The handles of many hand trowels forks, rakes, and weeders are made of smooth wood with small diameters that can be slippery, necessitating increased force in the hand, wrist, and arms for effective use.

2.3. MUSCLE ACTIVITY

Intermittent gripping work is a frequent activity in industrial work. The basic function in gripping is the finger flexion activated by the finger flexors in the forearm. However, in order to maintain a straight wrist, the wrist extensors have to be activated to counteract the wrist flexion torque caused by the finger flexion tendons as demonstrated by Snijders et al. (1987) and Hägg and Milerad (1997). However, these investigations only provided qualitative data. An important issue is to know the degree of exertion in the involved muscles.

Another important task is to assess repeated gripping work in order to identify potentially risky work regimes for contracting musculoskeletal disorders (Kilbom, 1994). In ergonomic research accurate monitoring of most of these processes or of the force producing capacity itself is often not possible, because of practical or ethical limitations. Therefore, changes of the surface- electromyogram (EMG), as easily obtainable indicators of muscle activities, have become increasingly popular over the past decades.

2.3.1. The Role of Oxygen in Muscle Actions

Muscle fibers are activated by nerve impulses within the muscle bundles. Those impulses trigger a complex series of enzyme and chemical reactions that result in muscle fiber contraction.

20 Oxygen is needed in this process and is brought from the lungs to the muscle by its blood supply.

Carbon dioxide resulting from chemical reactions during contractions of the muscle bundles is simultaneously carried away by blood to the lungs. When oxygen is not in sufficient supply, lactic acid builds up in the muscle bundle until more oxygen is available. Typically in sudden start-ups of an activity, the resident oxygen supply is used up and the current blood supply has not delivered enough oxygen, so some lactic acid builds up in the muscles. This is known as the

“oxygen debt” phase.

With increases in the blood flow, oxygen is delivered fast enough to reduce the level of lactic acid in the bundle. The increased blood supply typically continues after the physical effort has stopped in order to remove all of the lactic acid. This is known as the “repayment with interest” phase. Many capillaries located between the muscle fibers deliver blood to the activated fibers. Arterioles (small arteries) branch from the arteries to bring blood to the capillaries, and venues (small veins) pick up blood from these capillaries for transport back to the blood veins.

Blood is directed to those arterioles and venues away from resting muscle bundles so that there is more blood available to working muscle bundles.

If working muscles are contracted too much or for too long, they cannot get an adequate supply of blood and oxygen. Lactic acid accumulates in the affected muscles, and they may become painful. Work designs that call for the application of excessive forces over long time periods must therefore be avoided. This is especially true for back muscles. Another issue is that rigid, unnatural postures can cause muscles in the back, neck, and elsewhere to become painful.

For this reason, postural freedom is an important principle of workplace design. It also follows that when extensive physical exertion is necessary, rest periods are required to balance the muscular effort.

21 2.3.2. Physical Work Assessment by Heart Rate

There is close interaction between the metabolic processes and their support systems: for proper functioning, the working muscles or other metabolizing organs must be supplied with nutrients and oxygen, and metabolic byproducts must be removed (Kroemer et al., 2010). The heart powers the transport system, blood circulation. Therefore, heart rate (HR), a primary indicator of circulatory functions, and oxygen consumption representing the metabolic conversion have a linear and reliable relationship in the range between light and heavy work, as sketched in

Figure 2-6. Given this relation, one often can simply substitute heart rate measurements for measurement of metabolic processes, particularly O2 assessment.

Measurement of heart rate has another major advantage over oxygen consumption as indicator of metabolic processes: heart rate responds more quickly to changes in work demands, hence indicates more easily quick changes in body functions due to changes in work requirements

(Kroemer et al., 2010). The reliability of these techniques is limited primarily by the intra- and inter- individual relationships between circulatory and metabolic functions. Statistically speaking, the regression line (Figure 2-6), which associates heart rate with oxygen uptake, differs in slope and intersect from person to person and from task to task, and may change with training or disconditioning of a person.

2.3.3. Physical Work Assessment by Subjective Rating of Perceived Effort

Humans are able to perceive the strain that a given work task generates in their bodies and they can judge this perceived effort in absolute and relative terms. Certainly, assessing and rating the relationship between the physical stimulus and its perceived sensation have been used

22 as long as people have expressed their preference of one type of work over another (Kroemer et al., 2010).

Since the 1960s, formal techniques for “rating the perceived exertion” (RPE) associated with different kinds of efforts have been at hand. A common procedure is to appraise the effort on a nominal scale from “light” to “hard.” Such a verbally anchored scale also allows measuring the strain subjectively perceived while performing standardized work.

Figure 2-6: Scheme of the relationships between oxygen uptake and heart rate (Lehto and Buck, 2008)

2.4. WORK-RELATED MUSCULOSKELETAL DISORDERS

Work related musculoskeletal disorders (WMSDs), also known as Cumulative Trauma

Disorders (CTD), Repetitive Strain Injuries (RSI), or Overuse Syndrome, are a group of health problems caused by overuse or misuse of muscles, tendons and nerves. Generally, WMSDs can be classified into three basic types by anatomical characteristics: tendon and nerve disorders and muscle injuries. Tendon disorders occur at or near the joints where the tendons irritate nearby

23 ligament and bones. The tendons without sheaths are vulnerable to repetitive motions and awkward postures. When a tendon is repeatedly tensed, some of its fibers can tear apart. This makes the tendon inflamed, thickened and bumpy. Tendonitis is the general term indicating inflammation of the tendon. The most frequently noted symptoms are a dull aching sensation over the tendon, discomfort with specific movements and tenderness to touch. Recovery is usually slow and condition may easily become chronic if the cause is not eliminated (Lipscomb, 1995).

Muscle injuries arise from excessive force exertions and the mechanism of injury for muscle disorders is quite different from the tendon-related disorders. Typically, a muscle injury occurs as the result of excessive external forces on the passive structures, mainly connective tissues, rather than from overuse. An excessive contraction is another causation of the structural damage and loss of force generating capacity (McComas and Thomas, 1968). Nerve disorders occur when repeated or sustained work activities expose the nerves to pressure from hard, sharp edges of the work surface, tools or nearby bones, ligaments, and tendons (Feldman et al., 1983).

The symptoms include pain, tingling, and numbness in the hand. Carpal tunnel syndrome (CTS) is known to the most common nerve disorder. The carpal tunnel is formed by the bony carpal arch and the overlying transverse carpal ligament and flexor retinaculum. Common symptoms of CTS include pain, numbness, tingling and clumsiness in the affected area of the hand and fingers resulting in difficulties performing normal activities (Phalen, 1972). Careful job and hand tool designs and work place re-designs are recommended to reduce the incidence of CTS.

2.4.1. Risk Factors associated with WMSDs

The WMSDs of the distal upper extremities may result from the interaction between physical and personal factors. Specific risk factors of WMSDs are difficult to identify because

24 many risk factors may interact simultaneously to induce the condition (Moore, 1992; NIOSH,

1997).

Repetitive motions

There is strong evidence for a positive association between highly repetitive works and

WMSDs. Highly repetitive work may directly damage tendons with repeated stretching and elongation as well as increase muscle fatigue and decrease the time for fatigue recovery

Numerous studies identified repetitive motions as a risk factor associated with development of

CTS (Silverstein et al., 1987; Keyserling et al., 1993). Many workers perform the same tasks and stereotyped motions over and over, sometimes thousands or tens of thousands time each day.

Highly repetitive motions require fast muscle contractions, which become less efficient and demand greater recovery time because muscle capacity to produce force diminishes with increasing contraction speed. Silverstein et al. (1987) reported that odds ratios for risk of CTS and

CTDs were 1.9 and 3.6, respectively, in high repetition jobs compared to jobs that require a low number of repetitions. Based on these results, they indicated that jobs which have a basic cycle time of 30 seconds or less, and jobs in which over 50 percent of the work cycle are spent performing the same basic motions pattern have been associated with elevated rates of CTS.

Forceful exertion

The forceful exertion required to do the task plays an important role in the onset of

WMSDs. More force equals more muscular effort, and consequently, a longer time is needed to recover between tasks. Since in repetitive work, as a rule, there is not sufficient time for recovery, the more forceful movements develop fatigue much faster (Chaffin, 1973). Exerting force in

25 certain hand positions is particularly hazardous. The amount of force needed depends on the weight of the tools and objects that the worker is required to operate or move, and their placement in relation to the worker's body in manual material handling tasks (Keyseling et al., 1993).

Forceful exertions of the upper extremities (i.e., using knives, wrenches and other hand tools; using fingers and hands to shape or surface finish materials and parts, etc.) may cause upper extremity musculoskeletal disorders such as joint inflammation, muscle spasms, sprains, tendinitis, or diseases of the peripheral nerves (Armstrong et al., 1979; Silverstein et al., 1987).

Awkward posture

Awkward posture is one of the most frequently cited risk factors for CTS (Armstrong,

1978, 1994; Moore, 1992). Common examples of awkward wrist postures include excessive flexion, extension, radial and ulnar deviation, and pinch grips (Keir, 1999). Awkward postures overload muscles and tendons, loads joints in an asymmetric manner, thereby inhibiting blood flow (VanWely, 1970). The median nerve may be under considerable risk during awkward hand postures that place extreme pressure on the flexor tendon. In fact, sizable compressive forces have been demonstrated in the median nerve when hand movements involve simultaneous pinching and extreme wrist flexion (Rempel and Horie, 1994).

Gender

Gender had been indicated as a significant risk factor for the development of CTS as well as repetitive strain injuries (Tanzer et al., 1959; Kendall et al., 1960; Phillips et al., 1967; Phalen,

1972; Stevens et al., 1988). Ashbury (1995) demonstrated an average relative risk for reporting of repetitive strain disorders of 1.5 for women compared to men across all occupations but it was

26 much higher in some occupations: material handling (RR = 6.0), construction (RR = 4.0), processing (RR = 3.5). Enberg (1993) also indicated that women have anatomical and physiological differences that may place them at risk for farm injuries. The finding that women were more likely to have higher prevalence of repetitive strain injury than men is supported by the fact that women are, on average, shorter than men and have more adipose tissue, narrower shoulders, and smaller hands (Mackay and Bishop, 1984). Generally, the 50th and 95th percentiles of female functional measurements approximate the 5th and 95th percentile values for male measures (Phillips et al., 1981). On average, upper body strength is 40% to 75% less in females than in males, while lower body strength is 5% to 30% less in females (Falkel et al.,

1986).

There could also be a gender difference in the mechanisms underlying human response to pain although gender differences have been observed in tendon and ligament (Hart et al., 1998).

Data supporting such a hypothesis suggested that women did indeed perceive significantly greater pain from a standardized noxious cutaneous stimulus than men (Paulson, Minoshima, Morrow, &

Casey, 1998). Radwin and Lavender (1999) found that much of variation due to gender is due to underlying differences in strength capacities and anthropometric characteristics.

There may be relative differences in tolerance to biomechanical loads that explain the gender effect. For instance, Jager et al. (1991) found a difference in the static compressive strength of spine, with women having 25-30% less strength than men. Lindman et al. (1990, 1991) discovered that the fibers in the trapezius muscle differs between the genders, with women having more Type I fibers than men. It has been suggested that myofascial pain originates in the Type I fibers, thus this histological difference is a plausible explanation of the gender difference in muscle-based disorders. Furthermore, the smaller cross-sectional area of the trapezius muscle fibers for women may indicate a lower functional capacity that may play a role in the development of symptoms and disorders in the neck and shoulder region.

27 2.5. HAND ANATOMY & MECHNISM

The hand is the distal end of the upper extremity. It is made up of the thumb and finger metacarpals and phalanges. The hand is the key point of function for the upper extremity. The first digit, the thumb, has three joints: the carpometacarpal (CMC) joint, metacarpophalangeal

(MCP) joint, and interphalangeal (IP) joint (Figure 2-7).

Figure 2-7: Joints and bones of the fingers and thumb. Note that each finger has a DIP and PIP joint, whereas the thumb only has an IP joints (Lippert, 2006).

2.5.1. Ligament and Other Structures

Flexor Retinaculum Ligament. The flexor retinaculum ligament is a fibrous band that spans the wrist on the anterior surface of the wrist in a horizontal direction (Fig. 2-8). Its main function is to hold these tendons close to the wrist, thus preventing the tendons from pulling away

28 from the wrist (bow-stringing) when the wrist flexes. It also prevents the two sides of the carpal bones from spreading apart or separating.

Transverse Carpal Ligament. The transverse carpal ligament lies deeper and more distally. It attaches to the pisiform and hook of the hamate on the medial side and to the scaphoid and trapezium bones laterally. It arches over the carpal bones forming a tunnel through which the median nerve and nine extrinsic flexor tendons of the fingers and thumb pass. Figure 2-9 shows the bony floor of the carpal bones, the fibrous ceiling of the transverse carpal ligament.

Figure 2-8: The flexor retinaculum is made up of the palmar and transverse carpal ligaments (Lippert, 2006).

Extensor Retinaculum Ligament. The extensor retinaculum ligament is a fibrous band traversing the wrist on the posterior side in a horizontal mediolateral direction (Figure 2-10). It attaches to the styloid process of the ulna medially, and to the tri-quetrum, pisiform, and lateral side of the radius. It holds the extensor tendons close to the wrist, especially during wrist extension.

Extensor Expansion Ligament. The extensor expansion ligament, also called the extensor hood, (Figure 2-11) is a small triangular-shaped flat aponeurosis covering the dorsum and sides of

29 the proximal phalanx of the fingers. The extensor digitorum tendon blends into the expansion. It is wider at its base over the MCP joint, actually wrapping over the sides somewhat. As it approaches the PIP joint, it is joined by tendons of the lumbricales and interossei muscles. It narrows toward its distal end at the base of the distal phalanx. The extensor digitorum, lumbricales, and interossei muscles form an attachment to the middle and/or distal phalanx by way of this expansion. The extensor hood area, formed by the extensor expansion proximally, covers the head of the metacarpal and keeps the extensor tendon in the midline.

Carpal Arches. When the hand is relaxed, the palm assumes a cupped position. This palmar concavity is due to the arrangement of the bony skeleton reinforced by ligaments. There are three arches that are responsible for this shape (Figure 2-12). These arches contribute to the function of various types of grasp.

Figure 2-10: Extensor retinaculum (Lippert, 2006).

Figure 2-11: The extensor expansion provides an attachment on the middle and/or distal phalanx for several muscles (Lippert, 2006).

Figure 2-12: The three arches of the hand (Lippert, 2006).

2.5.2. Extrinsic Muscles

In addition to the wrist muscles, several other muscles not only span the wrist but also cross the joints in the hand as well. These muscles are called extrinsic muscles of the hand because their proximal attachment is above, or proximal to, the wrist joint. They have an assistive role in wrist function, but their primary function is at the thumb or finger. The main extrinsic muscles of the finger, which are involved in gripping an object, are flexor digitorum superficialis

(FDS) and extensor digitorum (ED) (Figure 2-13).

Figure 2-13: Flexor digitorum superficialis (left) and Extensor digitorum (right) (Lippert, 2006).

2.5.3. The Effect of Finger Extensor Mechanism

Finger mechanics is complicated by the so-called extensor mechanism. The extensor mechanism transmits force from the intrinsic muscles to the interphalangeal joints (Landsmeer,

1955; Tubiana, 1981). The extensor hood surrounding the MCP joint receives tendinous ﬁbers from the lumbricals and interossei, and therefore, the load transmitted to the extensor mechanism via the contraction of the intrinsic muscles produces PIP and DIP extension. The central tendon of extensor digitorum communis (EDC) attaches to the intermediate phalanges, where tension from tendinous expansion of intrinsic muscles extends the PIP joint. The lateral bands (radial band and ulnar band) proceed on the dorsal side of the PIP joint and merge over the dorsum of the intermediate phalanx, forming the terminal extensor (TE) slip and inserting into the distal phalanx, where tension results in the extension of the DIP joint. The lumbrical attaches proximally to the FDP tendon, and distally to the extensor mechanism, and hence, its activity

33 increases passive tension in the extensor mechanism and decreases passive tension in FDP tendon’s distal portion (Tubiana, 1984; Harding et al., 1993).

Figure 2-14: A schematic illustration of lateral view of the extensor mechanism (Li et al, 2001).

2.5.4. Interaction of Wrist and Hand Motion

Wrist motion is essential for augmenting the fine motor control of the fingers and hand.

Positioning the wrist in the direction opposite that of the fingers alters the functional length of the digital tendons so that maximal finger movement can be attained. Wrist extension is synergistic to finger flexion and increases the length of the finger flexor muscles, allowing increased flexion with stretch (Figure 2-15A) (Tubiana, 1984). Conversely, some flexion of the wrist puts tension of the long extensors, causing the fingers to open automatically and aiding full finger extension

(Figure 2-15B).

Figure 2-15: Role of wrist position in finger function. (A) Slight extension of the wrist allows the flexor muscles to attain maximal functional length, permitting full extension. (B) Slight flexion of the wrist places tension on the digital extensor tendons automatically opening the hand aiding full finger extension (Nordin and Frankel, 2001).

The synergistic movements of the wrist extensors and the more powerful digital flexors are facilitated by the architecture of the wrist. The digital flexor tendons cross the wrist within the depths of the carpal arch and are held close to the axis of wrist flexion-extension, affecting wrist position minimally. By contrast, the extrinsic wrist flexors and extensors are positioned widely about the periphery to provide maximal moment arms for positioning the wrist.

As the wrist changes its position and the functional lengths of the digital flexor tendons are altered, the resultant forces in the fingers vary, affecting the ability to grip. Volz and associates (1980) evaluated electromyographically the relationship of grip strength and wrist position. Grip strengths of 67, 134, 201, and 268 N were analyzed with the wrist in five postions:

40 and 20° of flexion, neutral, and 20 and 40° of extension. They found that grip strength was greatest at approximately 20° of wrist extension and least at 40° of wrist flexion. With the wrist in

40° of extension and in the neutral position, grip strength was slightly less than the maximal values.

35 Studies by Hazelton and coworkers (1975) of the influence of wrist position on the force produced at the middle and distal phalanges revealed that the greatest force was generated with the wrist in ulnar deviation, the next greatest in extension, and the least in palmar flexion. Taken together, the results of Volz and associates (1980) and Hazelton et al. (1975) suggest that for grip to be effective and have maximal force the wrist must be stable and must be in slight extension and ulnar deviation. This conclusion is consistent with the findings load transmission through the ulnar TFCC structures.

The position of the wrist also changes the position of the thumb and fingers, thus affecting the ability to grip. When the wrist is flexed with the hand relaxed, the pulp of the thumb reaches only the level of the DIP of the index finger; with the wrist extended the pulps of the thumb and index finger are passively in contact, creating an optimal situation for gripping or patching (Figure 2-16).

Hazelton et al. (1975) studied the effect of wrist position on the force produced by the finger flexors and reposted that the percentage distribution of the total force produced by the finger flexors to each individual finger bore a constant relationship regardless of the wrist

36 position. However, the magnitude of the total force did vary with the wrist position. In palmar flexion of the wrist the middle and distal phalanx produced least amount of force whereas maximum force was generated in ulnar deviation.

When exerting submaximal forces in a five-finger static pinch prehension. Radwin et al.

(1992) studied the contribution of individual fingers with 10%, 20%, and 30% of their maximal voluntary prehensile strength using spans of 4.5-6.5 cm. They also recorded total pinch force and individual finger forces while grasping a dynamometer supporting fixed weights of 1.0, 1.5, and

2.0 kg loads. They found that the average proportion of forces developed by the index, middle, ring, and little fingers were 33%, 33%, 17%, and 15% respectively. With increase in exertion level from 10% to 30% the contribution of the middle finger was not constant increasing from

25% to 38%. Such mechanical behaviors of different digits in the background of anatomical and mechanical information may hold a strategic clue to minimize these musculoskeletal afflictions.

2.5.5. Power Grip

Power grip or power grasp is a forceful act performed with the finger flexed at all three joints so that the object is held between the finger and the palm, with the thumb positioned on the palmar side of the object to force it securely into the palm (Figure 2-17). It is usually performed with the wrist deviated ulnarly and dorsiflexed slightly to augment the tension the flexor tendons.

Figure 2-17: The two fundamental patterns of prehensile hand function. (A) A typical power grip. The adducted thumb forms a clamp with the partly flexed fingers and the palm. The palmar descent of metacarpals IV and V and additional flexion in their respective MCP joints enable these fingers to hold the object firmly against the palm. Counter-pressure is applied by the thumb, which lies approximately in the plane of the palm. The wrist is deviated ulnarward and dorsiflexed slightly to increase the tension in the flexor tendons. Grip of an object along the oblique palmar axis (palmar groove), as shown here, involves a larger area of contact, and thus more control, than dose grip along the transverse palmar axis. (B) A typical precision maneuver. The object is pinched between the flexor aspects of the fingers and the thumb. The fingers are semiflexed and the thumb is abducted and opposed. The wrist is dorsiflexed (Landsmeer, 1955).

There are four phases of power grip: opening the hand, positioning the fingers, approaching the fingers or fingers and thumb to the object, and the actual grip. Each phase is a prerequisite of effective grip.

Opening Phase

Opening is an intuitive action and the amount is predetermined by an intent to grasp a specific object. The hand assumes a posture that will accommodate the physical structure of the object. Full opening is not required for grasping tasks in daily self-care activities but may be required for grasp in leisure or occupational tasks.

38 The position of the wrist influences the fingers and thumb. Wrist flexion permits full extension of the fingers (Tubiana et al., 1996; Smith et al., 1996) to open the hand for grasp of large objects. In this position the tip of the thumb is level with the PIP joints of the fingers

(Tubiana, 1984). As the distance between the open hand’s fingers and thumb encompasses excess space in relation to the object, the MCP joints of the fingers are often fully extended, whereas the

IP joints are always flexed to a certain degree so that the gripping surfaces of the fingers face the object (Benz, 1980).

The opening phase is a dynamic phase (Landsmeer, 1962), characterized by concentric muscle contraction. Active opening is achieved through the synergistic muscle action of the wrist flexors and the finger extensors (Kapandji, 1982; Norkin and Levangie, 1992; Smith et al., 1996;

Tubiana, 1984). The long extensors of the fingers extend the MCP joints and have a secondary wrist extensor action. To prevent the extensor action from occurring at the wrist, the wrist flexors function as counteracting synergists, keeping the wrist in a neutral position of flexion (Smith et al., 1996). The integrity of extensor digitorum is essential for creating active finger opening

(Benz, 1980). The larger the object to be grasped, the more the fingers abduct and thumb radially abducts and/or extends.

Finger and Thumb (Optional) Positioning Phase

The choice of finger position occurs in conjunction with the opening phase and adjustment to the desired position occurs at the MCP and IP joints (Landsmeer, 1962). The integrity of the activity of extensor digitorum in extending the MCP joints and lumbricales in creating a grip position is essential in this phase of grip (Benz, 1980). When ulnar deviation of one or more MCP joints is a component of the intended grip, the interossei replace the lumbricales.

39 Approach Phase

The movement pattern identified for this phase is wrist extension, finger and thumb flexion, and adduction. As in the opening phase, the position of the wrist influences the fingers and thumb. Wrist extension permits full flexion of the fingers (Tubiana et al., 1996; Smith et al.,

1996) as one grasps an object. As the object is approached, the fingers usually flex simultaneously and close around the object (Smith et al., 1996) so the palm of the hand contacts the object. Flexor digitorum profundus is the critical muscle used in free closing of the hand

(Long et al., 1970). The wrist extensors function to stabilize the wrist and prevent wrist flexion by profundus and superficialis (Smith et al., 1996). The thenar muscles, when the thumb is involved, are active as the thumb approaches the object for its final position of adduction and/or opposition.

Both the position and muscle activity are influenced by the shape of the object to be grasped.

Static Grip Phase

This phase is a power or stabilization phase and is characterized by isometric muscle contraction. The function of the hand complex is to stabilize an object, so that it can be moved by the proximal limb segments (Landsmeer, 1962) and contribute to the aggregate power of the arm.

The power grip has three significant characteristics: (1) the wrist is held in neutral or extension, (2) the fingers are maintained in flexion and abduction or adduction, and (3) the volar surfaces of the fingers and portions of the palm make forceful contact with the object. The thumb may or may not be included in the grip (Norkin and Levangie, 1992). For example, in grasping a briefcase the thumb does not contribute to the grip and this grip is referred to as a hook grasp. In grasping a cylindrical object, such as a hammer or a cup, the thumb does contribute to the grip.

When included for an element of precision, it is usually abducted and flexed.

40 The shape, size, and/or weight of the object influences the degree of finger flexion, the area of palmar contact, and thumb position. When grasping different sized cylinders, the DIP joint angle remains constant and the fingers adjust to the new cylinder size through changes in the joint angles at the MCP and PIP joints (Lee and Rim, 1991). It should also be noted that as the diameter of a cylindrical object increases, the total grip strength has been shown to decrease

(Radharkrishnan and Nagaravindra, 1993).

The ability of the two ulnar fingers to flex and rotate at the CM joints and flex beyond

90° at the MCP joints contributes to digitopalmar content on the ulnar side of the hand. Research by Bendz (1993) shows the hypothenar muscles, notably the flexor digiti minimi and the abductor digiti minimi, contract to flex the fifth metacarpal and proximal phalanx of the fifth digit. The abductor digiti minimi also rotates the fifth metacarpal. These muscles contract to provide strength to the grip, but for full strength the flexor carpi ulnaris is subsequently required to augment the contractions of the flexor and abductor digiti minimi via the common attachment of these muscles to the pisiform bone (Bendz, 1993). However, the ring and little finger can generate only 70% of the force of the index and middle fingers, so that power requirements fall to the radial fingers (Hazelton et al., 1975). As increased force is required in the grasp, the wrist ulnarly deviates. The greatest force generated at the phalanges is obtained when the wrist is in ulnar deviation (Hazelton et al., 1975). Within the general classification of Napier’s (1956) descriptors of power grip, various subgroups of postures can be identified. Kamakura and associates

(Kamakura et al., 1980) identify five patterns of power grip. These patterns have the three general characteristics previously specified. Specific patterns may be differentiated according to the involvement of the thumb, degree of range of movement, finger position, and/or the amount of digiopalmar contact area. Sollerman and Sperling (1978) developed a code system that classifies handgrips according to the participation of the various parts of the hand, the positioning of the fingers and joints, the contact surfaces, and the relationship between the longitudinal axis of the

41 object and the hand. The postural details described in both studies illustrate the immense variety of ways that one can grasp an object and the concomitant muscle activity that may exist in these postures.

Long and associates (1970) present electromyographic data of intrinsic-extrinsic muscle activity involved in five classifications of power grip: simple squeeze, hammer squeeze, screwdriver squeeze, disc grip, and spherical grip. The following summary of their findings provides insight into the muscle activity patterns involved in the static grip phase of hand posture.

The extrinsic finger flexors provide the major gripping force. Flexor digitorum profundus and superficialis both contribute to power grip with superficialis increasing its participation as force requirements increase. The major intrinsic participation is provided through the interossei.

They abduct or adduct the proximal phalanx to align the fingers with the object so that the extrinsic flexors can provide the gripping power. The interossei also provide gripping power as they flex the metacarpaophalangeal joints.

When the thumb is adducted and flexed in power grip, the muscle power is provided through the isometric contraction of adductor pollicis (Norkin and Levangie, 1992; Smith and

Weiss, 1996; Long and Conrad, 1970; Basmajian and DeLuca, 1985) and flexor pollicis longus

(Norkin and Levangie, 1992; Tubiana, 1984). Flexor pollicis brevis contributes to the stability required in a firm grasp (Tubiana, 1984; Basmajian and DeLuca, 1985).

Chapter 3

CASE STUDY - SHOVELS

3.1. INTRODUCTION

Interest in the design of farming and gardening tool and equipment does appear to be growing (Kumar, 1995). Digging and shoveling are common tasks in a range of industries including farming and horticulture as well as in leisure pursuits such as gardening (Bridger et al,

1997). Although digging can be defined as breaking, turning or excavating soil and shoveling as transferring loose material from one place to another, there is considerable overlap between the two tasks in practice (Bridger et al, 1997). In farming and gardening chores, digging and shoveling are manual handling tasks using hand tools such as shovels and spades, which would be presented to impose considerable stress on the musculoskeletal system of the user. Allread et al.

(2004) documented that many of these tasks were shown to have considerable risk of low back injuries. When working with a long-shafted tool, the low back is approximately in the horizontal position when starting the lift and maximum spine compression is reached directly (Hansson &

Öberg, 1996).

The 2007 Census of Agriculture showed that women have a growing presence in U.S. agriculture (USDA, 2009). National Gardening Association (NGA) reported that food gardening in the U.S. is on the rise (NGA, 2009). In total, 37 percent of all U.S. households, or an estimated

43 million households, plan to grow vegetables, fruit, berries, or herbs in 2009 compared with 31 percent, or an estimated 36 million households, in 2008 (NGA, 2009). This made 10 percent among households, mostly women active gardeners, plan to spend more time in food gardening during 2009. Of the expanded user population, women have also driven the need to develop more

43 ergonomic features for the tools used by both genders because women users are willing to pay more for increased ease and less discomfort (Sanders, 2004). Nonetheless, long-handled gardening tools such as shovels and spades have been designed for average men without specifically regarding women’s biomechanical and physiological differences, less muscle strength and smaller body dimensions than men.

Generally, the 50th and 95th percentiles of women functional measurements approximate the 5th and 50th percentile values for men measures (Phillips, Bogardt, & Pepper, 1981). The need for women to have tools and equipment designed for them becomes apparent when considering gender differences in terms of physical and physiological characteristics. These differences may place women at risk for farm injuries when using traditionally designed tools and cause an anthropometric mismatch which would make operators exert excessive muscle forces with awkward postures.

Many researches have been carried out on work physiology involved in shoveling. The task of shoveling was scientifically first examined by F. W. Taylor (1915), in his famous

Bethlehem Steel study of 1898, where he found an optimal shovel load of 9.8 kg. Freivalds

(1986a,b) reviewed the literature on shoveling and shovel design and indicated the following recommendations in shovel design by a series of experimental studies: a lift angle 32°, a large, square-point blade for shoveling, a round-point blade for digging, a hollow-back construction to reduce weight, a solid socket for strength in heavy duty uses, a step for digging in hard soil, and a long tapered handle.

Previous studies suggested that shovel design could be improved by fitting a second handle to the shaft of the shovel, thereby reducing the need to stoop (Sen, 1984; Degani, 1993;

Bridger et al., 1995). Degani et al. (1993) reported that the addition of a second handle lower on the shaft significantly reduced EMG activity of the back extensors, subjective rating of perceived exertion when digging, and bending reported by participants. Bridger et al. (1995) compared a

44 conventional spade with a levered spade based on participants’ lumbar positions, velocities and accelerations as well as their foot forces and posture for each type of spade. The results indicated that bending and the risk of low-back injury were reduced by 40 percent and 9 percent, respectively, with the levered spade. However, a tradeoff was found between the large reduction in stooping and the increase in lumbar twisting with the levered spade.

The handle traditionally has been of a T or D grip, but more recently the shape of grips has been varied by elongating and contouring the D grip either horizontally or vertically to accommodate multiple hand positions while shoveling and digging. Although the effect of handgrip type on shoveling has been reported less often in the ergonomics literature, many manufacturers of non-powered agricultural and garden tools are developing new grips to satisfy customers’ aesthetic needs and comfort.

This study consists of two parts that determined key design parameters for shovel design

(Phase I) and evaluated a redesigned shovel equipping new ergonomic design features as well as including user preference on the handle height, the distance between the top of handle and ground

(Phase II). The first purpose of the study in Phase I was to test the hypothesis that the lift angle

(12°, 24°, and 36°), addition of a second handle (attached and not attached), and type of handgrip

(Normal D, Elongated D, Contoured D) would have a significant effect on the physiological

(oxygen consumption, heart rate, and perceived exertion), kinematic (trunk posture), and performance (soil mass dug) variables. Shovels with ergonomic interventions are compared to a commercial shovel while controlling extraneous variables. The experiment was designed to take place in the laboratory where physiological parameters could be accurately measured while simultaneously controlling for extraneous variables. The second purpose of the study in Phase II was to determine an optimal handle height by including user preference and test the effects of blade type (square-point-flat-steel and bi-functional gooseneck), task type (digging and

45 transferring), and second handle position (fixed and preferred) on physiological, subjective, kinematic, and performance variables.

3.2. METHODS: PHASE I – DETERMINATION OF KEY DESIGN PARAMETERS

3.2.1. Participants

Nine healthy women participants participated in the study. Participant characteristics are shown in Table 3-1. They were all students who volunteered for the study and were paid appropriately for their work. Before the experiment, all participants were instructed about how typical digging tasks are performed with the standard procedures such as set position, dig, lift, and turn. The experimental procedures were explained to all participants after they signed an informed consent form. There was no participant who experienced any back and hernia problems in the past.

Table 3-1: Participant Characteristics (n = 9).

Variables Mean S.D.

Age (years) 27.0 2.1

Body Weight (kg) 53.2 3.3

Height (cm) 163.7 4.3

Resting Heart Rate (bpm) 79.0 5.7

3.2.2. Shovel Designs

Each participant used nineteen different shovel designs: a commercial shovel (Figure 3-1) and eighteen redesigned shovels. Common terms for shovel are represented in Figure 3-1.

Physical characteristics of shovels are shown in Table 3-2 where the commercial shovel is Code 1

46 and other eighteen new prototype shovels are indicated as Code 2 to 19. For all shovel designs, the square-point-flat steel blade was used to satisfy both digging and shoveling tasks. The shaft length was 94 cm for the commercial shovel and 70 cm for all redesigned shovels.

Figure 3-1: 3D lifting posture simulation for the participants from Penn State Women Agricultural Society.

To determine an appropriate total length for new prototype (or redesigned) shovels, a series of 3D Lifting Posture Simulations were conducted with four women professional farmers recruited from Penn State Women Agricultural Society. For the simulation, their average values of each joint angle during lifting were used. And the shaft length estimated from the simulation results was 46 cm between the left hand (holding handgrip) and the right hand (holding shaft) to lift the loaded shovel (Figure 3-1). The total shovel lengths, in turn, become 124.5 cm (Figure 3-

2) and 100.5 cm (Figure 3-3) for commercial and redesign shovel, respectively. For trials using the shovel with a second handle, the second handle was fitted at the main shaft as close as possible to each participant’s shoulder breadth. In other words, the distance between handgrip and

47 second handle was controlled within each participant’s shoulder breadth to minimize the excessive use of back flexion while shoveling.

Table 3-2: Physical characteristics of eighteen shovels.

Code Lifting Angle Second Handle Handgrip Weight (kg) 1 12° No ND 2.5 2 Yes ND 2.8 3 Yes ED 2.8 4 Yes CD 3.0 12° 5 No ND 2.5 6 No ED 2.5 7 No CD 2.7 8 Yes ND 2.8 9 Yes ED 2.8 10 Yes CD 3.0 24° 11 No ND 2.5 12 No ED 2.5 13 No CD 2.7 14 Yes ND 2.8 15 Yes ED 2.8 16 Yes CD 3.0 36° 17 No ND 2.5 18 No ED 2.5 19 No CD 2.7

Figure 3-2: Configurations for commercial shovel and common terms for shovel components.

Figure 3-3: Configurations for new prototype shovels.

3.2.3. Experimental Design

The experimental design was a 3×3×2 full factorial design for the evaluation of three levels of the lifting angle condition (12°, 24°, and 36°), two levels of the addition of second handle condition (attached and not attached) (Figure 3-4), and three levels of the handgrip condition (Normal D, Elongated D, and Contoured D) (Figure 3-5). The order of the eighteen test conditions was randomly assigned.

A Student’s paired t-test was used to determine differences between the physiological, kinematic, and subjective variables when using either the commercial shovel or the shovel with optimal conditions, which were found from the ANOVA results. Probability values of p < 0.05 were accepted as being statistically significant.

Figure 3-4: Second handle attachment.

Figure 3-5: Shovel handgrip conditions. Normal (left). Elongated D (middle). Contoured D (right).

3.2.4. Experimental Procedures

Each participant’s experimental session consisted of one digging task following typical four-step procedures such as set position, dig, lift, and turn. Three minutes of work were followed by three minutes of rest. During rest, the participant’s heart rate was taken to check whether the participant had recovered from fatigue within the range of each participant’s first resting heart rate ± 5 bpm (Åstrand et al., 2003). The first two minutes of work were used as a warm-up to reach a steady state, while the last minute was used for data collection.

The order of the eighteen test conditions was randomly assigned for each participant to start the experiment. Participants’ body weight and stature were measured when they arrived. The tasks were performed in a foundry (Figure 3-6), using foundry-casting sand that was regularly moistened as well as checked its density with a soil penetrometer to maintain uniform consistency. The total session lasted approximately 3 hours. In all cases, the rate of digging was kept constant by a metronome at 20 scoops/min based on the recommendations by Freivalds

(1986a) and the weight of the last ten scoops was taken to estimate each participant’s shoveling performance.

Figure 3-6: Shoveling simulated laboratory setting.

3.2.5. Measurements

The volume of oxygen consumption (VO2) was normalized to body weight and to shoveling performance in order to obtain a normalized aerobic capacity and energy cost. This followed the procedure of Freivalds (1986b) and allowed one to minimize the effects both of body size and of individual variation in performance of the task. Heart rate was also normalized to each participant’s resting heart rate.

52 Oxygen uptake

During the trial, the volume of oxygen consumption (VO2) was collected every second via a respiratory gas analyzer of the expired air, using the Qubit’s BBB1LP, Breath by Breath

Respirometry Package (Figure 3-7), and averaged using Logger Pro software via a LabPro interface that was compatible with both PC and Macintosh Computers.

Figure 3-7: S147 rapid response O2/CO2 analyzer (Qubit Systems Inc.).

Heart rate

The heart rate was collected via S182 Wireless Exercise Heart Rate Monitor (Figure 3-8) every 5 seconds using a Polar Electrode and transmitter/receiver system to transfer heart rate data to the LabPro Interface. The participant’s average heart rate was calculated from the collected raw data.

Figure 3-8: S182 wireless heart rate monitor (Qubit Systems Inc.).

53 Subjective rating

The participant was asked to map discomfort body regions after the shovel used.

Subjective ratings of the perceived exertion (RPE) of the shoveling task were measured. This rating, developed by Borg (1973) is a scale from 0 to 10, which has been used successfully to evaluate discomfort in the body.

Performance

Shoveling performance was calculated from the amount of sand of the last ten scoops in the basket per unit time (kg/scoop).

Trunk flexion

Trunk flexion during shoveling was calculated by projecting screen captures on a 2×2 mm grid. Calculation was based on angles measured from videos recorded of participants in critical postures assumed during the tasks (Figure 3-9).

Figure 3-9: Projected posture estimation on a 2 by 2 mm grid.

3.3. RESULTS

Of the three lift angles, the steepest angle, 36°, was preferred by six of the eight participants. The most common reasons given for the preference were the perception that it made the digging easier with less kicking force and bending of the trunk. Of the three handgrips, five of the eight participants preferred the elongated D grip. The main reasons given for the preference were more room to grip the handle since it is designed by horizontally stretching the normal D grip approximately twice. Of the two conditions of the second handle, seven of the eight participants preferred the addition of it to the main shaft. The common reasons given for the preference were less bending of the trunk and effort when lifting the soil. One participant preferred the shovel without the second handle because the second handle was less efficient in the

55 amount of soil moved while shoveling. The mean perceived exerting ratings were similar for all conditions. The descriptive statistics are represented in Table 3-3.

Table 3-3: Descriptive statistics for the eight shoveling conditions.

Variable Lift angle Handgrip Second handle

12 deg. 24 deg. 36 deg. ND ED CD N Y Mean Mean Mean Mean Mean Mean Mean Mean

(S.D.) (S.D.) (S.D.) (S.D.) (S.D.) (S.D.) (S.D.) (S.D.) Physiologic VO2 0.268 0.245 0.233 0.249 0.244 0.254 0.253 0.245 [ml/min/kg/kg] (0.015) (0.018) (0.014) (0.020) (0.023) (0.020) (0.022) (0.020) Heart rate 1.777 1.720 1.663 1.709 1.731 1.720 1.790 1.649 [avg. bpm/rest bpm] (0.149) (0.138) (0.154) (0.160) (0.168) (0.134) (0.131) (0.142) RPE 5.438 5.368 4.938 5.104 5.563 5.076 5.032 5.463 [0 to 10] (1.956) (1.918) (1.606) (1.689) (1.886) (1.917) (1.896) (1.757) Efficiency Shoveling 1.465 1.686 2.126 1.637 1.767 1.873 1.839 1.679 performance (0.149) (0.231) (0.287) (0.269) (0.348) (0.409) (0.370) (0.328) [kg/scoop] Posture Trunk flexion 67.220 63.870 59.390 64.830 62.360 63.290 69.699 57.284 [degree] (9.540) (8.840) (8.450) (10.380) (8.930) (9.020) (7.350) (6.926)

The results of ANOVA conducted on VO2 data found significant differences in lift angle, handgrip, and addition of the second handle. The 36° lift angle, elongated D grip, and addition of the second handle required less energy cost while shoveling. No significant interactions between the factors were found for VO2 data. Reduced heart rate was found with the 36° lift angle and normal D grip. For RPE, the interaction between lift angle and second handle factors was significant. The combination of 36° lift angle with second handle addition was given lowest subjective ratings by the participants. The effects of three factors on the shoveling performance were well explained by the experiment. The results on shoveling performance data indicated significant differences in lift angle, handgrip, addition of the second handle, and the interaction between lift angle and handgrip. The design parameters such as 36° lift angle, elongated D grip, and second handle addition were contributory factors to increase the shoveling performance. The

56 average trunk flexion when lifting was significantly decreased by the shovel design of 36° lift angle with the addition of second handle. Among factors analyzed and some their interactions, there is a consensus that 36° lift angle, elongated D grip, and second handle addition are influential parameters to make the shoveling task more efficient. The full results of ANOVA for the experimental design are included in Table 3-4.

Table 3-4: Results of ANOVA to 3*3*2 factorial designs.

Second Lift angle Handgrip Variable Handle (1)×(2) (1)×(3) (2)×(3) (1)×(2)×(3) (1) (2) (3) F(2,143) = F(2,143) = F(1,143) = F(4,143) = F(2,143) = F(2,143) = F(4,143) = VO2 62.04 5.19 8.47 0.74 0.44 1.31 0.26 p = 0.000 p = 0.007 p = 0.004 p = 0.566 p = 0.644 p = 0.273 p = 0.903 F(2,143) = F(2,143) = F(1,143) = F(4,143) = F(2,143) = F(2,143) = F(4,143) = Heart rate 9.56 0.37 43.74 2.15 0.97 1.63 0.69 p = 0.000 p = 0.692 p = 0.000 p = 0.079 p = 0.381 p = 0.199 p = 0.597 F(2,143) = F(2,143) = F(1,143) = F(4,143) = F(2,143) = F(2,143) = F(4,143) = RPE 1.11 1.13 2.11 1.52 4.26 0.15 1.10 p = 0.332 p = 0.326 p = 0.149 p = 0.200 p = 0.016 p = 0.859 p = 0.357 Performa F(2,143) = F(2,143) = F(1,143) = F(4,143) = F(2,143) = F(2,143) = F(4,143) = nce 170.35 21.09 29.07 7.18 1.18 1.23 0.56 p = 0.000 p = 0.000 p = 0.000 p = 0.000 p = 0.309 p = 0.296 p = 0.693 Trunk F(2,143) = F(2,143) = F(1,143) = F(4,143) = F(2,143) = F(2,143) = F(4,143) = flexion 18.66 1.87 139.60 3.24 0.19 0.02 0.44 p = 0.000 p = 0.158 p = 0.000 p = 0.014 p = 0.827 p = 0.983 p = 0.779

Table 3-5 shows the paired t-test results of the analysis of same variables in ANOVA above for the shoveling task using the two shovels: (1) commercial shovel in Figure 3-2 and (2) redesigned shovel with optimal design parameters (RedesignOPT) such as 36° lift angle, elongated

D grip, and second handle addition. Average oxygen consumption (VO2), perceived exertion, and trunk flexion when lifting were found to be significantly different for the commercial shovel compared to redesigned shovel (p < 0.05).

Table 3-5: Results of paired t-test: Commercial vs. RedesignedOPT Shovel.

Variables Commercial Shovel RedesignOPT Shovel p value (12 deg., ND) (36 deg., ED & SH)

Mean S.D. Mean S.D.

VO2 (ml/min/kg/kg) 0.245 0.023 0.224 0.013 0.022

Heart Rate (avg. heart rate / rest heart rate) 1.548 0.131 1.663 0.133 0.111

RPE (Borg scale, CR-10) 6.8 1.8 4.8 1.7 0.019

Shoveling performance 20.525 1.728 19.203 1.928 0.239

Trunk flexion 74.4 9.2 53.9 7.8 0.000

3.4. DISCUSSION AND CONCLUSIONS

It is concluded that shoveling and digging tasks are associated with relatively high physiological load and stressful working postures in terms of lower back. Traditional or commercial long-handled agricultural hand tools such as shovels and spades have been designed for men users. This problem would cause an anthropometric mismatch of tool configurations with working postures and make women more vulnerable to musculoskeletal disorders due to their relatively smaller body dimensions and less strength. The results showed that the three design features such as 36° lifting angle, ED, and SH improve the work of shoveling by reducing required physiological costs such as VO2, heart rate, RPE, and the degree of trunk flexion.

Shoveling with the second handle, however, is not likely to enhance the shoveling performance.

Nevertheless, there was a consensus that those three design features are key design parameters for a new shovel design because the second handle significantly reduced the trunk flexion. The introduction of the redesigned shovel with optimal ergonomic design parameters (36 deg., ED &

SH) can make the shoveling work require less energy cost as well as more upright posture. These kinds of interventions on shovel/spade reduce biomechanical and physiological loads on them.

58 The t-test results in Table 3-5 indicated that the shoveling performance did not significantly differ between the two designs although other tested variables, VO2 and RPE, were significantly improved by the redesigned shovel with the three key design features than the commercial shovel.

In addition to the performance, many participants were still dissatisfied with the shorter shovel length of redesigned shovel. Thus, the next prototype built in Phase II focuses on these two factors by including user preference on handle height and developing a new shape of blade.

3.5. METHODS: PHASE II – EVALUATION OF NEW PROTOTYPE OF SHOVEL

In this work, a new prototype of shovel was constructed with a bi-functional gooseneck blade, which has rounded tip and curved socket while keeping the 32° lifting angle. To determine an appropriate shovel length for the new prototype, women’s preferred handle height was measured from the nine women participants in Phase I. This methodology was adapted from the study by Garneau and Parkinson (2007) investigating the height of seat top of an exercise cycle.

The effect of second handle position was also investigated whether it is fixed at a biomechanically balanced position (at the upper end of socket) or whether it is attached to a preferred position by each participant.

3.5.1. Determination of Optimal Handle Height Including User Preference For New Prototype Shovel

Selecting key anthropometric measurements

During the experiment in Phase I, all relevant measures of the shovel length, stature, trochanteric height, acromion-radiale length, radiale-sylion length, and preferred handle height, were taken for the nine women participants (Figure 3-10 and Table 3-6). Each participant was

59 asked to naturally stretch the arms and then put the hands on the top of the handgrip where this posture is recommended to fully utilize the leverage in the biomechanical aspect (Figure 3-10).

After completing this procedure, a preferred handle height, the distance between the hands and ground was measured for each participant. A stature adjustment of 25 mm was included to account for the thickness of shoes.

Figure 3-10: Method to determine preferred handle height and its relevant anthropometric measurements.

Table 3-6: Summary of nine women anthropometric measurements taken from Phase I. (unit: mm)

Trochanteric Acromion-Radiale Radiale-Stylion Preferred Participant Stature Height Length Length Handle Height

1 1708 840 305 243 705

2 1749 885 322 257 775

3 1544 749 291 222 575

4 1700 940 300 250 790

5 1600 775 275 220 545

6 1626 895 290 245 698

7 1630 895 290 230 750

8 1630 895 310 235 760

9 1700 900 300 253 720

* All nine participants were women

Based on the 1988 U.S. Army Anthropometry survey for women, the measurements ranged from 9th percentile to 96th percentile for stature, 1st percentile to 81st percentile for trochanteric height, 9th percentile to 73rd percentile for acromion-radiale length, and 6th percentile to 80th percentile for radiale-stylion length, respectively.

To select key body dimensions, a classifying linear regression analysis was performed with cross-validation to define the relationship between the measured body dimensions and preferred handle height. The preferred handle height was used as Y variable, and stature, trochanteric height, acromion-radiale length, and radiale-stylion length were used as X-variables.

From the linear regression analysis, both stature and trochanteric height were selected as significant predictors that can be considered as key body dimensions and the regression equation is statically significant (p < 0.05) in the following

PHHWOMEN = 0.285 (SWOMEN) + 1.08 (THWOMEN) - 394 where PHH is the preferred handle height, S is stature, and TH is the trochanteric height. R2 for the regression is 0.881 and RMSE is 34.5 mm. Figure 3-11 shows the plots of preferred handle height versus stature and trochanteric height.

Figure 3-11: Preferred handle height plotted against stature and trochanterion for the 9-women participant sample, with regression line.

Although men’s preferred handle heights were not investigated due to the limitation that all participants in Phase I were women, the above equation could explain that stature and trochanteric height are not only dominated factors to predict the preferences on the handle height, but also contributory factors indicating women specific operating strategy to lower the handle height around or below their trochanteric heights. Section 3.5.6 will discuss more about this in detail.

Generation of virtual population sample for NHANES

The NHANES data were selected over ANSUR as the basis for U.S. women population since they were gathered more recently (2007-2008 vs. 1988) and are a civilian (vs. military for

ANSUR) population. Importantly, they are expected to reﬂect the increased prevalence of obesity in the U.S. population. To use the most recent population data, a random sample of 1,000 virtual women users, which ranged from 20 to 59 years, was generated from the NHANES (2007-2008) database. The random sample generation was performed by Minitab with the mean stature, 163.9 cm, and standard deviation, 6.9 cm. To avoid a potential effect from diverse ethnicity, the mean

62 and standard deviation were extracted from the only white women data. These two parameters for white women in the database were used as inputs to get the stature values. Figure 3-12 shows the distribution of stature of the 1000 virtual white women users generated from the database. The mean and standard deviation of the distribution were 164.1 cm and 6.6, which were almost identical to the mean of all women ranged from 20 to 59 years in NHANES (2007-2008). This new population is termed NHANESWOMEN for the rest of this chapter.

Figure 3-12: Distributions of 1000 random stature values in the NHANESWOMEN.

Extrapolation of body measures from ANSUR to NHANES

For the predictor, trochanteric height, a linear regression model was created in Minitab with the S (stature) values, in the ANSUR database for women. The equation for the resulting regression model is given by

TH = 0.601(SANSURWOMEN) – 117.5 + N (0, 24.2)

63 where R2 for the regression is 0.714 and RMSE is 24.2 mm. Then, the trochanteric height for

NHANESWOMEN could be derived using the same coefficients for the stature and terms for the constant and residual error by

TH = 0.601(SNHANESWOMEN) – 117.5 + N (0, 24.2)

The S and BMI for the population in NHANESWOMEN could be obtained from the given database and the procedure was created a random sample generation technique with Minitab. Table 3-7 shows that women trochanteric heights in NHANESWOMEN are consistently a little bit smaller than those from ANSUR for all percentiles.

Table 3-7: Trochanteric height comparison of NHANESWOMEN with ANSUR.

Percentile ANSUR NHANESWOMEN NHANESWOMEN/ANSUR 5 791 765 0.968

10 806 782 0.971

15 817 794 0.972

20 824 803 0.974

25 830 810 0.976

30 837 818 0.977

35 843 824 0.978

40 849 831 0.979

45 854 837 0.980

50 861 843 0.979

55 866 849 0.981

60 872 855 0.981

65 879 861 0.980

70 885 868 0.981

75 892 876 0.982

80 899 883 0.983

85 909 894 0.983

90 921 906 0.984

95 939 926 0.986

64 Hybrid Anthropometric Model with Residual Variance

The method of a term representing the residual variance, which describes deviations from the mean, was applying a preference component for the regression model. It gives

PHHNHANESWOMEN = 0.285 (SNHANESWOMEN) + 1.08 (THNHANESWOMEN) - 394 + N (0, 33.9)

Figure 3-13 represents the 3D scatter plot of the stature, trochanteric height, and preferred handle height when the preference is included.

Figure 3-13: Stature, trochanteric height, and preferred handle height estimated for NHANESWOMEN with including preference.

If adjustability can be applied for the design process, the accommodation of 95 percent of

NHANESWOMEN population would be achieved by targeting an appropriate span, which is typically 2.5th to 97.5th-percentile portion of the distribution. Table 3-8 summarizes preferred handle height and shaft length by selected percentile values and their adjustability ranges. For a mid-sized new prototype of shovel in Phase II, the shaft length for 50th percentile women, 1145 mm, was adopted.

Table 3-8: Preferred handle height, shaft length for selected percentile.

Percentile Preferred Handle Height [mm] Shaft Length [mm]

2.5 814 962

50 965 1145

97.5 1130 1329

3.5.2. Participants

Eight healthy graduate students (4 men and 4 women) participated in the study. All participants have had some experience in shoveling, generally in gardening or military trenching activities. All participants have no history of low-back pain the previous 6 months and all volunteered for the study. To avoid a potential size effect in terms of stature, each participant was screened by the percentiles of ANSUR women data. The mean stature was 163.8 ± 2.7 cm for men and 163.7 ± 4.0 cm for women. The mean weight was 63.7 ± 4.8 kg for men and 60.6 ± 6.7 kg for women. The stature ranged from the 35th to 74th percentiles for men and from the 26th to

81st percentiles for women, based on the ANSUR women. There was considerable overlap in terms of stature and weight between men and women participants. Individual participant characteristic is given in Table 3-9.

Table 3-9: Participant characteristics (Phase II)

ANSUR Women %iles Gender Age Weight [kg] Stature [cm] (Stature)

35 M 29 58.7 160.4

60 M 31 63.1 164.5

54 M 32 62.7 163.3

74 M 27 70.2 167.0

55 W 25 60.4 163.5

58 W 28 60.9 164.0

81 W 27 68.8 168.6

26 W 27 52.3 158.8

3.5.3. Experimental Design

Ten different design conditions were evaluated (Table 3-10) including two tasks (digging and shoveling), two blades (bi-functional gooseneck and square-point-flat-steel), two second handle conditions (fixed at a biomechanically balanced position and preferred by participants).

The bi-functional gooseneck blade was newly designed with the round shape of blade with raised edges, curved long socket, and larger footsteps while keeping the same optimal 36-degree-lift angle (Figure 3-14). Ergonomic advantages of equipping the bi-functional gooseneck blade with the shovel are assumed (1) to assist lifting the shovel out from the ground after it is embedded, (2) to bring the shovel handle closer to the center of body without much sacrificing the 36° lifting angle, (3) to optimize both digging and shoveling (or scooping) by rounded blade with raised edges, and (4) to transfer much larger amount of kicking force by the larger footstep. The overall length of new prototype shovel in Phase II was designed for mid-sized women by introducing the user preference, which was estimated in Section 3.5.1. The condition of the second handle (with and without) was investigated and the biomechanically balanced position of second handle was initially determined by the first-class lever system (Figure 3-15) that was very close to the upper

67 end of socket. Before testing, each participant’s preferred second handle position was asked and its effect was compared with the position estimated from the first-class lever system.

Table 3-10: Experimental conditions in Phase II.

Run Task Blade Lift Angle Second Handle

1 Fixed Bi-functional Second 2 36 Preferred Gooseneck 3 Digging No Second -

4 Square-point 36 Second Preferred 5 -flat-steel 12 No Second -

6 Fixed Bi-functional Second 7 36 Preferred Gooseneck 8 Shoveling No Second -

9 Square-point 36 Second Preferred 10 -flat-steel 12 No Second -

Figure 3-14: Bi-functional round-point-gooseneck long socket blade.

Figure 3-15: Position for the second handle attachment by the first-class level system.

3.5.4. Experimental Procedures

Two different tasks, digging and shoveling, were asked for participants to perform. For the digging task, the participants stood on a flattened sand pile, dig into the sand, lifted the shovelful slightly and turned the sand at a side to pile them for the shoveling task. The shoveling task consisted of scooping sand from the sand pile and throwing it into a basket beside of the participant. The amount of sand carried during each trial was measured on a scale to normalize the shoveling performance.

During testing, each participant performed the two different tasks where each task consisted of five different design combinations (Table 3-10). Five minutes of work were followed by 10 min of rest. The first 2 min of work was used as a warm-up period to reach a stead state, while the last 3 min was used for data. The order of the ten trials could not be fully blocked because the digging task was performed first to pile sand for the shoveling task, but the order was fully randomized within each task. For the data analysis, two-sample t-tests and a multivariate analysis of variance (MANOVA) were conducted to examine the effects of Gender, Task, Second

Handle and their interactions on the dependent measures collectively. If statistical significance of

69 the MANOVA (p < 0.05 for the Wilks’s Lambda statistic) was found for a main effect (or interaction), then that effect (or interaction) was further tested using interaction plot of data means for each measure. When significant effects of the second handle were detected, a

Bonferroni post-hoc analysis was performed to further refine the understanding of the significant effects. Measurements, assessments, and equipment used in Phase II were same with those in

Phase I except that the degree of knee flexion was measured at the moment of lifting.

3.5.5. Results

The effect of shovel type on physiological and subjective variables

A two-sample t-test was used to investigate any statistically significant mean differences between shovel types for the oxygen consumption, heart rate, perceived exertion, perceived discomfort, and perceived fatigue. All values of measured variables were expressed as means and standard deviation. Probability values of p < 0.05 were accepted as being statistically significant.

Table 3-11 and 3-12 show the results of the analysis of the variables. Except for the normalized heart rate between the best-redesigned shovel with 36° lifting angle, elongated D grip, and second handle attachment in Phase I (RedesignedPHASE(I)) and best-redesigned shovel with bi-functional gooseneck blade and fixed second handle position in Phase II (RedesignedPHASE(II)), all variables are significantly different in terms of their mean values by the shovel design. For most of variables, working with the RedesignedPHASE(II) shovel showed improved physiological and kinematic responses and better performance than those of the commercial and RedesignedPHASE(I) shovel.

70 The effect of gender on the degree of knee flexion

A two-sample t-test was used to investigate any statistically significant mean differences between genders for the degree of knee flexion at the moment of lifting. All values of measured variables were expressed as means and standard deviation. Probability values of p < 0.05 were accepted as being statistically significant. Table 3-13 shows the results of the analysis of the variables.

Table 3-11: The effect of shovel type on physiological and subjective variables (Commercial vs. RedesignedPHASE(II))

Variables Commercial Shovel RedesignedPHASE(II) p-value Mean S.D. Mean S.D. Oxygen Consumption 8.07 1.85 5.12* 0.96 0.000 (ml/min/kg/kg) Normalized Heart Rate in % 185.7 17.9 167.0* 11.4 0.002 (avg. heart rate / rest heart rate) Perceived Exertion 13.21 2.37 9.17* 2.66 0.000 (Borg scale, CR-20)

Normalized Perceived Discomfort in % 67.9 12.7 25.1* 8.92 0.000

Normalized Perceived Fatigue in % 62.5 17.9 22.38* 4.97 0.000

*. Significant at the level .05.

Table 3-12: The effect of shovel type on physiological and subjective variables (Best in Phase I vs. Redesigned shovel)

Variables RedesignedPHASE(I) RedesignedPHASE(II) p-value Mean S.D. Mean S.D.

Oxygen Consumption (ml/min/kg/kg) 7.37 1.65 5.12* 0.96 0.004

Normalized Heart Rate in % 175.5 17.2 167.0 11.4 0.086 (avg. heart rate / rest heart rate)

Perceived Exertion (Borg scale, CR-20) 13.13 2.39 9.17* 2.66 0.002

Normalized Perceived Discomfort in % 69.6 20.4 25.1* 8.92 0.000

Normalized Perceived Fatigue in % 59.1 10.9 22.38* 4.97 0.000

*. Significant at the level .05.

Table 3-13: The effect of gender on the degree of knee flexion at the moment of lifting.

Variables Men Women p-value

Mean S.D. Mean S.D.

Knee Flexion (degree) 15.07 10.82 49.97* 16.71 0.000

*. Significant at the level .05.

The effect of task type and second handle on physiological and subjective variables within bi- functional gooseneck blade shovel experiment

The MANOVA results for the perceived (or subjective), performance, and physiological measures showed a significant effect of Gender, Task, Second Handle, and their two-way interactions, but not their three-way interaction (Table 3-14).

For the subjective variables (Perceived Exertion, Discomfort, and Fatigue), the shoveling task consistently made users (for both genders) more discomfort, exertion, and fatigue than digging task. It is because the shoveling task involved some degree of trunk rotation. Except for

Perceived Fatigue, the perferred second handle position by participants reduced perceived force

72 discomfort and exertion levels (Figure 3-16 and 3-17). For both genders, those perceived levels were minimized when the second handle was fixed at the biomechanically balanced position. It was also found that men participants felt more fatigue when the second handle is fitted to the preferred point than when second handle was not given, but the case was opposite for women participants (Figure 3-18).

For the physiological variables (oxygen comsumption and heart rate), women participants required less physiological costs than men participants for both tasks, digging and shoveling. It was directly related to less shoveling performance of women participants (Figure 3-19). The position of the second handle was found to be statistically significant for the physiological measures. When the second handle was fixed to the mechanically balanced point, the amount of oxygen consumption and the heart rate during both tasks were minimized (Figure 3-20 and 3-21).

It was interesting to note that women’s physiological responses bewteen the work with preferred second handle postion and without second handle did not differ significantly, but the physiological responses were significantly lowered with preferred second handle postion for men.

The average preferred postion of second handle were 59.7 cm (± 7.8 cm) for women and 17.5 (±

10.9 cm) for men where the position was measured by upward direction from the upper end of socket. As the position of second handle is getting closer to the handgrip (or getting further from the upper end of socket, which is the biomechanically balanced point), users should lose a large amount of lifting balance.

Table 3-14: Results of MANOVA.

Effect Wilks' Lambda Value F Hypothesis df Error df Sig.

Intercept 0.001 5231.056 6 25 0.000

G * 0.193 17.445 6 25 0.000

T * 0.005 836.799 6 25 0.000

SH * 0.000 315.716 12 50 0.000

G×T * 0.330 8.443 6 25 0.000

G×SH * 0.191 5.357 12 50 0.000

T×SH * 0.010 37.021 12 50 0.000

G×T×SH 0.511 1.660 12 50 0.105 G: Gender, T: Task, SH: Second Handle * Significant at the level .05.

Figure 3-16: Interaction plot (data means) for Perceived Discomfort.

Figure 3-17: Interaction plot (data means) for Perceived Exertion.

Figure 3-18: Interaction plot (data means) for Perceived Fatigue.

Figure 3-19: Interaction plot (data means) for Shoveling Performance.

Figure 3-20: Interaction plot (data means) for Oxygen Consumption (VO2).

Figure 3-21: Interaction plot (data means) for Normalized Heart Rate.

3.5.6. DISCUSSION AND CONCLUSIONS

In this study, various physiological and subjective measurements were investigated for the effects of task type, blade shape and second handle conditions. The redesigned shovel in

Phase II, which equipped the bi-functional gooseneck blade and fixed position of second handle had significantly positive influences on oxygen consumption and perceived exertion, discomfort, and fatigue levels for men, but not all for women. Women gave lowest ratings

The shaft length of redesigned shovel (1145 mm) in Phase II was shorter than that of conventional shovel (1245 mm) about 100 mm. Table 3-16 shows the adjustability range of shaft length, 367 mm, which is calculated from the data in Table 3-8 to accommodate of 95 percent of

NHANESWOMEN population. This indicates the shaft length of conventional shovel, 1245 mm, could be too long for average women users because the length corresponded to a 90th percentile woman’s preferred handle height. Although including user preference in the design process could provide much larger accommodation for the targeted women population, advanced manufacturing techniques and materials should be required for a potential trade-off between durability and adjustability in terms of the shaft. It should be carefully considered in the design for any striking hand tools such as shovel, spade and hoe. In spite of that, the final design solution to maximize biomechanical advantages and satisfy most of potential users would be the preference-included adjustability if manufacturing can support appropriate sizing of the tools.

Table 3-15: Adjustability ranges from preferred handle height and shaft length for selected percentiles.

Percentile Range Adjustability Range of Shaft Length [mm]

2.5 to 97.5 1329 - 962 = 367

For gender-specific lifting strategy, there was a clear difference in terms of knee flexion between men utilizing fully curved back with flatten knee and women flatten back with flexed

78 knee (Figure 3-22). The t-test result showed that women flexed their knees 25 degree more on average than men when lifting the loaded shovel (Table 3-13). On the biomechanical aspects

(Figure 3-23), women try to take shorter moment arms for both body weight and the loaded shovel by bending their knees and flatten backs so that the compressive force on L5/S1 disc can be significantly reduced. Men, however, take different strategy maximizing the leverage by bending fully their backs and flatten knees. This technique should impose much larger amount of compressive force on L5/S1, but the imposed compressive force could be shared with the knees through force transferring body mechanism at the final stage of lifting.

Figure 3-22: Lifting strategy by men and women.

These understandings were agreed with the 3D simulation results for the participants

(Figure 3-24 and 3-25). On average, the compressive force that was imposed on women’s L5/S1 was 20 percent less, an estimated 463 N, than that of men.

Figure 3-23: Schematic diagram of moment arms and forces acting on L5/S1 while lifting (left). Lifting strategies differentiated by gender (right).

Figure 3-24: 3D simulation results of observed women lifting strategy in Phase II.

Figure 3-25: 3D simulation results of observed men lifting strategy in Phase II.

Chapter 4

CASE STUDY – PRUNING SHEARS

4.1. INTRODUCTION

Workers using hand-held tools subject their upper extremity to biomechanical stress and strain. Numerous studies indicate a strong correlation between upper extremity cumulative trauma disorders (CTDs) and forceful exertions. The effects are more severe, if forceful exertions are accompanied by high frequency and awkward postures (Silverstein et al., 1986; Armstrong et al.,

1986; Putz-Anderson, 1988; Kroemer, 1989). The effort to generate the required task force level is, among other factors, a function of tool design parameters. It has been indicated by past research that tool design may play significant role in the development of work-related disorders in the hand and forearm (Tichauer, 1966; Tichauer and Gage, 1978; Meagher, 1986, 1987;

Aghazadeh and Mital, 1987; Schoenmarkhlin and Marras, 1989a,b; Mital, 1991). CTDs reported from hand tool use include nerve entrapment, epicondylitis, peritendinitis of the forearm and tenosynovitis in the wrist and fingers (Kurppa et al., 1979; Armstrong et al., 1982).

The design, evaluation, selection and use of hand-held tools, therefore, are major concerns of the professionals in the field of ergonomics. The size of the grip span of a hand-held tool, among other design parameters, has been hypothesized as a “critical” factor not only contributing to the CTD risk factors but also performance of the workers (e.g., Cotten and

Bonnell, 1969; Greenberg and Chaffin, 1976; Petrofsky et al., 1980; Pheasant and Scriven, 1983;

Eastman Kodak Company, 1986; Kilbom et al., 1991; Fransson and Winkel, 1991; Eksioglu,

1996, 1999; Blackwell et. al., 1999).

Isometric grip contractions, performed with parallel handles, have been investigated by a number of researchers (e.g., Bechtol, 1954; Hertz- berg, 1955; Montoye and Faulkner, 1965;

81 Cotten and Bonnell, 1969; Cotten and Johnson, 1971; Petrofsky et al., 1980; Pheasant and

Scriven, 1983; Ergonomics Group of Eastman Kodak, 1986; Eksioglu, 1996, 1999; Blackwell et al., 1999). Majority of these studies described an optimal separation as a function of maximal force output. The optimum span, according to these studies (excluding Eksioglu, 1996, 1999), varies between 3.8 and 6.4 cm depending on experimental design, equipment and gender.

Päivinen et al. (2000) commented that a comprehensive list of the most important design criteria for plier-like hand tools is still lacking although several studies on hand tool evaluation and design have been published. Operation of some of these tools demands high grip, push or hand–handle contact force, which is known to be one of the primary factors that increase the risk of cumulative trauma disorders (Rempel et al., 1992; Reidel, 1995).

One of plier-like hand tools, pruning shear, is typically used with one hand and held the upper or palm handle pressing on the line joining the base of the thumb to the hypothenar area while the lower handle is activated by fingers’ flexion (Päivinen et al., 2000). Wakula et al.

(2000) indicated that pruning requires repetitive handgrips and wrist movements combined with static work in the upper arm-shoulder system, but little ergonomic information is available to assess physical load precisely during pruning. Grapevine pruning, for example, often requires very precise cutting to give the vine its orientation during the development of vine shoots and grape and the pruning task involves hard repetitive manual work over 4 to 5 consecutive months

(Roquelaure et al., 2002).

When gripping an object, the hand exerts a force resulting in a pressure on the hand. This is significant for gripping actions with the fingers that require simultaneous external forces acting upon two or more segments of each of the fingers as they co-operate to produce the desired function (Amis, 1987). Perceived pain in the hand, caused by high local external pressure, is often a limiting factor during work with hand-held tools (Fraser, 1980; Yun et al., 1992). In addition, high local pressure to the hand may result in blistering (Fraser, 1980; Yun et al., 1992) and the

82 discomfort caused by high pressure may reduce both the efficiency of the work and the consumer's satisfaction with the tool (Yun et al., 1992).

Fransson-Hall and Kilbom (1993) found greater contact area might reduce the chances for discomfort or pain from high pressure or pinch. Seo and Armstrong (2008) indicated that greater contact area can reduce average pressure for a given normal force on the hand because average pressure is the ratio of normal force magnitude to contact area. For the cylindrical handgrip, Seo et al. (2007) suggested that maximum grip/normal force can be achieved when the fingertips and thumb tip work together against the palm, thus resulting in great reaction force on the palm. For manual pruning shear design, however, these ergonomic principles of power grip are not potentially allowed due to the diagonal cutter handle shapes and no role of the thumb finger.

Bylund and Burström (2006) evaluated the effect of gender and handle size on the ability to perform a precision task and on ratings of discomfort and difficulty. The study found that handle size, anthropometric measures, and maximum grip strength influenced the women participants’ results and ratings more than the men participants.

Tool design plays an important role as far as the incidence of work-related problems or disorders when the hand and forearm is concerned. Improvements in the ergonomic properties of hand tools may be essential for the users’ safety and health (Redfern, 1992; Sperling, 1993). The aim of this study is, therefore, to show the needs of the ergonomic interventions for existing manual pruning shears and investigate the effects of pruning shear design, gender, and hand size on subjective hand discomfort and satisfaction, muscle activity, and grip force distribution over the hand regions.

83 4.2. METHODS

4.2.1. Participants

Twelve participants (6 men and 6 women) between the ages of 20 and 36 yrs (mean =

28.9±5.1) were recruited through advertisements within the Pennsylvania State University community. Each participant was paid at a rate of $7.00 per hour for participation. The participants, who all claimed to be right-handed, were all healthy volunteers and free of known musculoskeletal disorders and injuries. Ten of the twelve participants had at least gardening experience with manual pruning shears. At the beginning of the experiment, informed consent was obtained and anthropometric measurements of the hand were taken (Table 4-1).

4.2.2. Anthropometric Measurements

In addition to measuring participants’ height and weight, eight measurements followed or were modified from traditional anthropometric definitions (Roebuck et al., 1975; Greiner, 1991;

Pheasant and Haslegrave, 2006). Each digit link length for digit 2 (index finger) to 5 (little finger) was measured as the distance from the tip of digit to the proximal transverse palm crease

(Figure 4-1). This measurement was a modified functional digit link length when compared to the traditional definition, the distance between the tip of the digit and the first metacarpo-phalangeal joint, by Greiner (1991) because the upper handle was positioned along with the line of proximal transverse palm crease during actual usage (Figure 4-2). The functional length of the first digit, digit 1 link length, was calculated as the distance between the tip of the digit and the base of the first metacarpal, as approximated by the thenar crease (Figure 4-1). Hand length, the longest dimension of the hand, was measured as the perpendicular distance from the tip of digit to the

84 wrist crease base line (Figure 4-1). The width of palm was measured at the level of the metacarpo-phalangeal joints of the digits 2 and 5 with the fingers adducted (Figure 4-1).

Figure 4-1: Visual description of hand measurements.

Participants were divided into three categories according to their hand length. The categorical limit values were followed or modified from the values recommended by Oh and

Radwin (1993). Hand length up to 17.51 cm was classified as small, between 17.51 cm and 19.00 cm as medium, and greater than 19.00 cm as large. A hand length of 17.51 cm corresponded to a

40th-percentile woman or a 2.3-percentile man. A hand length of 19.00 cm corresponded to an

88th-percentile woman or a 35th-percentile man (Greiner, 1991). Participating in this experiment were twelve students: 6 men and 6 women. After the ten participants were randomly recruited, 3 were classified as having large hands, 4 as medium, and 3 as large. Based on their hand length,

85 one additional small-handed women and another one additional large-handed men were recruited to have the same number of participants in each size and gender category. Individual participant characteristic is given in Table 4-1.

Figure 4-2: Position of the upper handle during actual usage.

Table 4-1: Summary of participant characteristics

Hand Palm Mean Grip Hand Thumba Thumbb Indexb Middleb Ringb Littleb Gender Length Width Strength Size [cm] [cm] [cm] [cm] [cm] [cm] [cm] [cm] [N] M 7.40 12.90 9.57 10.64 11.13 11.07 16.75 10.15 377.8 ± 5.8 W 6.25 11.00 9.97 10.29 11.78 10.08 17.81 8.31 257.8 ± 4.4 S W 6.00 10.60 8.82 10.38 11.04 9.21 16.70 8.00 216.3 ± 5.1 W 5.86 10.20 9.40 10.35 10.85 9.80 16.10 7.90 197.1 ± 5.1 M 7.56 13.30 10.64 11.87 12.21 9.69 18.56 10.09 390.4 ± 16.1 M 7.23 12.70 9.93 10.28 11.35 9.47 17.90 9.80 370.4 ± 6.8 M W 6.82 11.70 10.41 10.97 12.10 10.07 17.93 8.67 317.1 ± 2.6 W 6.40 11.20 9.36 10.71 11.60 10.19 18.24 8.28 290.4 ± 2.6 M 7.00 12.30 11.41 12.33 13.11 10.46 20.04 9.55 342.3 ± 7.7 M 6.54 11.70 10.29 11.66 12.64 11.39 19.23 9.09 321.5 ± 11.2 L M 6.38 11.50 10.90 11.05 12.15 10.86 19.67 8.93 296.3 ± 2.6 W 7.16 12.20 10.36 11.50 12.53 10.91 19.65 9.00 327.5 ± 2.6 a finger length b finger link length

86 4.2.3. Experimental Design

Analyses of variances (ANOVA) were conducted for the pruning shear design, gender, and hand size to evaluate their effects on (1) user’s subjective rating on discomfort level of hand region, (2) satisfaction level of handle design, (3) EMG activity of FDS and ED muscles, (4) grip force distribution over the fingers, phalanges and palm regions, and (4) wrist deviations in F/E and U/R. Pearson’s correlation coefficients were calculated between maximum grip strength and hand anthropometric measures. Stepwise regression models were conducted to choose the best-fit predictors of hand anthropometric measures for subjective satisfaction rating and muscle activity.

Three pruning shear designs (Figure 4-3), which have different upper handle shapes were evaluated: (1) commercial pruning shear (CP), (2) rubber grip-padded pruning shear (RGP), and

(3) thumb grip-attached pruning shear (TGP).

Figure 4-3: Hand-powered pruning shear designs. [Left] commercial pruning shear (CP). [Middle] rubber grip-padded pruning shear (RGP). [Right] thumb grip-attached pruning shear (TGP).

The CP was a conventional bypass-pruning shear (Model # 6945, Fiskars) used as a reference in this study. The RGP was the newly designed model, which equips with a padded upper handle to minimize the force localization by maximizing the contact area between the handle surface and the palm side of thenar/hypothenar regions (Figure 4-4). A 7mm-thick foam rubber was padded around the inner handle of the pruner. The TGP was another newly designed model, which equips with a thumb support that is placed just after the grip guard as well as with a

87 guard to prevent the thumb finger from slips during work. The thumb support consists of a rubber grip and a universal adapter, which fits to the upper handle for almost of commercial pruners

(Figure 4-6). The new features of TGP were based on a critical design problem on the CP that the thumb finger is not involved in the grip motion while pruning.

Figure 4-4: Localized force on the palm side aligned with the thumb finger.

Figure 4-5: Thumb finger remaining passively during operating the pruning shear.

Figure 4-6: Schematic view of the thumb grip attachment.

4.2.4. Experimental Procedures

The maximum voluntary contraction (MVC) of both FDP and ED muscles was recorded before the pruning tests. The MVC of the FDP muscle was measured by Jamar hand dynamometer. Each handle of dynamometer was wrapped by flexible and trimmable force sensing resistors to measure the magnitude of contact force between the handles and palmar side of the hand while measuring each participant’s maximum grip strength (Figure 4-7). The maximal

EMG response for ED muscle was measured as the participant sat in front of a table. The participants’ arm was on a 90° angle on the side of the body with the lower arm at the table. Then the participant was asked to raise her or his hand as the researcher opposed the movement. The participants had three attempts, lasting for 2-3 seconds and the highest recorded value (µV) was used in analysis and the test contraction should last less than 5 seconds as Jonsson (1978) recommended.

Figure 4-7: The Jamar hand dynamometer where each handle is wrapped by force sensing resistors.

The participants were asked to execute 16 cuts with the three pruning shears after calibration where the cutting frequency was controlled with 1 cut per 8 seconds by a metronome.

Each cutting period was followed by a rest period of 2 minutes. Before pruning shears were changed, there was a 5-minute rest period. To obtain homogenous measuring conditions, the material for cutting was a 10 mm-wooden dowel and its length of 122 cm. The selected diameter,

10 mm, was based on previous studies: the diameter for normal grapevine was less than 20 mm

(Wakula et al., 2000) and 5 to 12 mm for branches in regional vineyards in Italy (Romano, 2010).

The wood was kept in water for two days before measurements so that the moisture content would resemble with natural wood. The laboratory setting for simulated pruning tasks is shown in

Figure 4-8.

Figure 4-8: Pruning simulated workstation.

4.2.5. Instrumentation and Apparatus

Force glove system

To evaluate the amount of total grip force and relative distribution of individual finger/palm force, a force glove system was developed by overlaying twelve flexible and thin

(FlexiForce Sensor, A101-25; Tekscan Inc., Figure 4-9) and three flexible and trimmable

(FlexiForce Sensor, 1235; Tekscan Inc., Figure 4-10) conductive polymer pressure sensors over the pre-determined hand regions (Figure 4-11). The location of these sensors was determined and identified by a small pilot study with four participants while they were naturally gripping the CP without cutting tasks.

Figure 4-9: The FlexiForce A101 sensor, has a sensing area of 0.375 in. (9.533 mm) and can measure forces up to 25 lbs.

Figure 4-10: The FlexiForce 1235 OEM trimmable sensor and can measure forces up to 100 lbs.

Figure 4-11: Force glove system and sensor locations.

Electromyographic measurement system

The electromyographic (EMG) activity of flexor digitorum superficialis (FDS) and extensor digitorum (ED) were collected by using FlexCompTM (Thought Technology Ltd.) at a sampling rate of 64 Hz from bipolar electrodes (MyoScan-Pro Sensor T9401M-60); EMG signals were filtered through a high-pass filter with a cutoff frequency of 8 Hz. The surface electrodes were positioned over the bellies of the primary digit flexor, FDS, and the primary extensor, ED, parallel to the longitudinal axis of these muscle fibers as recommended by Zipp (1982). To eliminate any effects on background noise and minimize between participant and electrode differences, the EMG was standardized (sEMG).

Movements of the dominant wrist

A twin axis goniometer (SG65; Biometrics Ltd.) attached on the dorsal surface, one end over the third metacarpal, the other over the midline of the forearm, with the wrist in the neutral position was used to collect wrist motion data in the flexion/extention (F/E) and ulnar/radial

(U/R) planes. Recordings of wrist deviation angles and EMG signal were synchronized and monitored on the same data logger. Wrist angles were defined and measured according to clinically accepted standard (Roquelaure et al., 2002).

4.3. RESULTS

4.3.1. Analysis of Anthropometric Variables

Anthropometric data for all participants is summarized in (Table 4-2). With the exception of age all anthropometric values revealed significant differences between men and women (p <

93 0.05). Variability in anthropometric characteristics was relatively consistent between the two genders. The hand length ranged from 1st percentile to 75th percentile for men, and from 2nd percentile to 95th percentile for women based on the hand anthropometry of U.S personnel data from Greiner (1991).

Table 4-2: Summary statistics for anthropometric variables.

Women (n = 6) Men (n = 6)

Mean ± Std. Dev. (Min - Max) Mean ± Std. Dev. (Min - Max)

Age (years) 27.7 ± 7.1 (20 - 36) 30.2 ± 2.3 (27 - 33)

Height (cm) 166.3 ± 6.1 (160 - 177) 174.2 ± 6.5 (165 - 183)

Weight (kg) 55.8 ± 5.5 (48.2 - 62.4) 66.3 ± 6.1 (60 - 77)

Thumb finger length (cm) 6.42 ± 0.47 (5.86 - 7.16) 7.02 ± 0.46 (6.38 - 7.56)

Thumb finger link length (cm) 11.12 ± 0.70 (10.16 - 12.2) 12.34 ± 0.67 (11.45 - 13.30)

Index finger link length (cm) 10.17 ± 0.59 (9.28 - 11.11) 10.92 ± 0.58 (10.11 - 11.91)

Middle finger link length (cm) 11.06 ± 0.58 (10.48 - 12.09) 12.07 ± 0.56 (11.28 - 12.74)

Ring finger link length (cm) 11.85 ± 0.56 (11.19 - 12.83) 12.86 ± 0.54 (12.00 - 13.67)

Little finger link length (cm) 10.21 ± 0.54 (9.60 - 11.50) 11.12 ± 0.51 (10.42 - 11.76)

Hand length (cm) 18.25 ± 0.94 (17.11 - 19.74) 19.46 ± 0.82 (18.30 - 20.41)

Palm width (cm) 8.36 ± 0.39 (7.90 - 9.00) 9.61 ± 0.47 (8.93 - 10.15)

4.3.2. Maximum Grip Strength and Anthropometric Variables

Maximum grip strengths were measured by using a Jamar dynamometer at a fixed 8.0 cm grip span when recording the MVC of FDP muscle. The force data for all participants are summarized in Table 4-3. Maximum grip force, averaged over the three repetitions for individual participant, was 353.39 N (Std. Dev. = 24.17 N) for men and 262.27 N (Std. Dev. = 43.63 N) for women where the average strength was 26% greater for men than for women. One-way ANOVA revealed that gender had a significant influence on maximum grip strength (Table 4-4).

Table 4-3: Summary of maximum grip strength data by gender.

Mean Std. Deviation 95% Confidence Interval for Mean Min Max

Lower Bound Upper Bound

Men 353.39 24.17 341.38 365.41 320.06 382.29

Women 262.27 43.63 240.57 283.97 200.03 315.61

Total 307.83 57.83 288.26 327.40 200.03 382.29

Table 4-4: One-way ANOVA result for maximum grip strength by gender.

Sum of Squares df Mean Square F Sig.

Between Groups 74736.90 1 74736.90 60.079 0.000

Within Groups 42295.48 34 1243.99

Total 117032.38 35

Hand size also had a significant influence on maximum grip strength (Table 4-5 and 4-6).

Post hoc tests of Bonferroni multiple comparisons indicated that sizes, small versus medium and small versus large did differ significantly in terms of maximum grip strength although medium versus large did not differ significantly for maximum grip strength (Table 4-7).

Table 4-5: Summary of maximum grip strength data by hand size.

Mean Std. Deviation 95% Confidence Interval for Mean Min Max

Lower Bound Upper Bound

Small 256.71 53.38 222.79 290.63 200.03 320.06

Medium 315.61 43.43 288.02 343.20 262.27 364.51

Large 351.17 30.62 331.71 370.63 315.61 382.29

Total 307.83 57.83 288.26 327.40 200.03 382.29

Table 4-6: One-way ANOVA result for maximum grip strength by hand size.

Sum of Squares df Mean Square F Sig.

Between Groups 54625.73 2 27312.867 14.443 0.000

Within Groups 62406.64 33 1891.11

Total 117032.38 35

Table 4-7: Bonferroni multiple comparisons for maximum grip strength.

(I) Hand Size (J) Hand Size Mean Difference (I-J) Sig. 95% Confidence Interval

Upper Bound Lower Bound

Small Medium -58.90(*) 0.007 -103.68 -14.12

Large -94.46(*) 0.000 -139.24 -49.68

Medium Small 58.90(*) 0.007 14.12 103.68

Large -35.56 0.160 -80.34 9.22

Large Small 94.46(*) 0.000 49.68 139.24

Medium 35.56 0.160 -9.22 80.34

* The mean difference is significant at the .05 level.

Correlation coefficients between anthropometric measurements and maximum grip strength are shown in Table 4-9. Disregarding the little finger link length, all anthropometric hand measurements were positively correlated (p < 0.01) with maximum grip strength (Table 4-8).

Finger length-related measures, finger link lengths, finger lengths and hand length, were highly inter-correlated among them and showed relatively weak or moderate correlation with maximum grip strength (Table 4-8). The highest correlation value was found between maximum grip strength and palm width (R2 = 0.942, p < 0.001) (Table 4-8). The strong relationship between maximum grip strength and palm width was further analyzed using two curve estimation regression models (quadratic vs. linear). Although a strong quadratic relationship between contact force and grip strength was found in Table 4-9 (R2 = 88.3%, Std. Error = 21.82), the relationship could be best described with a linear regression model due to its F-test statistic (220.14) is much

96 larger than that of quadratic model (124.20) (Table 4-9 and Figure 4-12). The linear regression model is given in the following equation:

!"# = 70.47 !" − 327.53 where MGS is the maximum grip strength and PW is the palm width. The palm width alone could explain 86.6% of the variance in maximum grip strength.

Table 4-8: Pearson’s correlation matrix for maximum grip strength and anthropometric variables.

Grip IF Link MF Link RF Link LF Link Hand Palm Strength Length Length Length Length Length Width Pearson 1 .523(**) .503(**) .436(**) 0.313 .446(**) .942(**) Grip Correlation Strength Sig. 0.001 0.002 0.008 0.063 0.006 0.000

Pearson .523(**) 1 .788(**) .867(**) .404(*) .831(**) .491(**) IF Link Correlation Length Sig. 0.001 0.000 0.000 0.014 0.000 0.002

Pearson .503(**) .788(**) 1.000 .888(**) .435(**) .777(**) .467(**) MF Link Correlation Length Sig. 0.002 0.000 0.000 0.008 0.000 0.004

Pearson .436(**) .867(**) .888(**) 1.000 .506(**) .926(**) 0.324 RF Link Correlation Length Sig. 0.008 0.000 0.000 0.002 0.000 0.054

Pearson 0.313 .404(*) .435(**) .506(**) 1.000 .510(**) 0.280 LF Link Correlation Length Sig. 0.063 0.000 0.008 0.002 0.001 0.099

Pearson .446(**) .831(**) .777(**) .926(**) .510(**) 1.000 .329(*) Hand Correlation Length Sig. 0.006 0.000 0.000 0.000 0.001 0.050

Pearson .942(**) .491(**) .467(**) 0.324 0.280 .329(*) 1.000 Palm Correlation Width Sig. 0.000 0.000 0.004 0.054 0.099 0.050

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed). IF, MF, RF, and LF indicate Index, Middle, Ring, Middle, and Little finger.

Figure 4-12: Curve fit for maximum grip strength.

Table 4-9: Curve estimation regression model summary and parameter estimates.

Equation Model Summary Parameter Estimates Std. Error of R Square F df1 df2 Sig. the Estimate Constant b1 b2

Linear 0.866 220.14 1 34 0.000 22.96 -327.53 70.47 - Quadratic 0.883 124.20 2 33 0.000 21.82 -1291.41 288.30 12.21

The independent variable is Palm Width

98 4.3.3. Grip Force and Contact Force

At a fixed 8.0 cm grip span, average total contact force on Jamar dynamometer handles was approximately 2.3 times greater than maximum grip strength (Table 4-10). Although a strong quadratic relationship between contact force and grip strength was found in Table 4-11 (R2 =

0.749, Std. Error = 29.19), the relationship could be best described with a linear regression model due to its F-test statistic (88.47) is much larger than that of quadratic model (49.23) (Table 4-11 and Figure 4-13). The linear regression model is given in the following equation:

!" = 0.32(!") − 58.42 where GS is the grip strength and CF is the contact force (Table 4-11 and Figure 4-6). The grip strength for women more proportionally increases than that of men as the palm width is getting larger (Figure 4-13).

Table 4-10: Summary of maximum grip strength and total contact force data.

Min Max Mean Std. Dev.

Contact Force 436.55 1107.38 785.84 159.02

Grip Strength 191.14 408.96 308.76 59.60

Table 4-11: Curve estimation regression model summary and parameter estimates.

Equation Model Summary Parameter Estimates

R Square F df1 df2 Sig. Std. Error of the Estimate Constant b1 b2

Linear 0.722 88.471 1 34 0.000 30.15 58.42 0.32

Quadratic 0.749 49.232 2 33 0.000 29.19 -131.41 0.84 0.00 The independent variable is Contact Force.

The dependent variable is Grip Strength.

Figure 4-13: Jamar grip strength as a function of contact force by gender.

4.3.4. Subjective Ratings

A MANOVA was conducted to examine the effects of Pruning Shear Design, Gender,

Hand Size and their interactions on the dependent measures, subjective satisfaction of grip force requirement and grip span, collectively. If statistical significance of the MANOVA (p < 0.05 for the Wilks’ Lambda statistic) was found for a main effect (or interaction), then that effect (or interaction) was tested using individual ANOVA for each measure. A randomized complete block design was used in this statistical analysis with “participant” acting as the blocking variable, thereby controlling for the high levels of inter-individual variability.

100 Discomfort by Hand Regions

The MANOVA results for the hand discomfort ratings by the eight pre-determined hand regions (Figure 4-14) showed a significant effect of both Pruning Shear and Gender, but not their interactions (Table 4-12). For any pruning shears and hand sizes, women consistently felt more discomfort on fingers, thenar, and wrist regions than men. The discomfort level of finger region was significantly increased when using CP when compared to TGP and RGP (Figure 4-15).

Participants rated the RGP as least discomfort, TGP as little discomfort, and CP as significantly discomfort handle. The average discomfort levels were 5% (men) and 12.2% (women) for RGP,

30.2% (men) and 35% (women) for TGP, and 59.8% (men), 75.5% (women) for CP (Figure 4-

15). For the thenar region, the discomfort level was significantly increased for both medium hand-sized participants and use of CP and minimized for both small hand-sized participants and use of RGP (Figure 4-16). It was interesting to note that the discomfort levels on thenar region were quite constant through different genders and hand sizes (hand lengths) when the participants used RGP (Figure 4-16). For the wrist region, the least discomfort level was obtained when men participants used TGP (10.7%) and when women participants used RGP (18.2%) (Figure 4-17).

The perceived discomfort on the wrist was extreme for women participants using CP (89.7%)

(Figure 4-17).

101

Table 4-12: Results of MNOVA and ANOVA for subjective hand discomfort rating data. Each cell is represented as F-statistic (p-value).

Effect MANOVA Thumb Fingers Metacarpal Thenar Hypothenar Wrist Heel

10.018 3.182 23.647 2.637 32.891 0.361 70.599 1.864 PS (.000) * (.066) (.000) * (.099) (.000) * (.702) (.000) * (.184)

4.243 0.378 3.621 0.004 5.813 0.597 9.106 3.802 G (.014) * (.547) (.077) (.953) (.027) * (.450) (.007) * (.067)

1.298 0.981 1.887 0.233 5.850 0.631 2.220 0.231 HS (.278) (.394) (.180) (.795) (.011) * (.543) (.137) (.796)

1.836 0.282 0.428 0.003 0.347 0.420 7.264 1.660 PS×G (.092) (.758) (.659) (.997) (.711) (.663) (.005) * (.218)

1.125 0.187 0.474 0.232 0.930 0.571 3.132 0.194 PS×HS (.355) (.942) (.754) (.917) (.468) (.687) (.040) * (.938)

1.114 0.322 0.953 3.066 0.083 0.291 1.776 0.337 G×HS (.395) (.729) (.404) (.071) (.921) (.751) (.198) (.718)

0.895 0.201 0.413 0.790 0.505 0.303 0.085 0.313 PS×G×HS (.617) (.934) (.797) (.547) (.733) (.872) (.986) (.866)

PS: Pruning Shear, G: Gender, HS: Hand Size (categorized by hand length) * Significant at the level of p < .05.

Figure 4-14: Investigated hand regions for subjective discomfort rating.

102

Figure 4-15: Subjective discomfort rating on finger region by gender and pruning shear.

Figure 4-16: Interaction plot (data means) for subjective discomfort rating on thenar region (y-axis: subjective discomfort rating [%]).

103

Figure 4-17: Interaction plot (data means) for subjective discomfort rating on wrist region (y-axis: subjective discomfort rating [%]).

Pruning Shear Design Satisfaction

The MANOVA results of the subjective satisfaction ratings for grip force requirement and grip span showed a significant effect of Pruning Shear, Gender or Hand Size, but not their interactions (Table 4-13). For the two pruning shears, CP and TGP and any hand sizes, women consistently felt less satisfaction in terms of those two dependent measures than men (Figure 4-

18). The average satisfaction level of grip force requirement was 88.2% for RGP, 51.4% for TGP, and 31.3% for CP, respectively (Figure 4-19). It was interesting to note that women participants were more satisfied than men when using the RGP, but not using other two pruning shears. As expected, the perceived satisfaction for grip span was significantly decreased, as users’ hand sizes were getting smaller (Figure 4-20). The average satisfaction level of grip span was 79.1% for the large hand-size group, 55.7% for the medium hand-size group, and 30.1% for small hand-size group, respectively (Figure 4-21). ANOVA results showed that the mean differences were statistically significant (p = .000).

104

Table 4-13: Results of MNOVA and ANOVA for subjective design satisfaction rating data. Each cell is represented as F-statistic (p-value).

Effect MANOVA Grip Force Requirement Grip Span

9.398 27.911 2.363 PS (.000) * (.000) * (.123)

10.154 0.832 21.422 G (.001) * (.374) (.000) *

32.028 0.047 191.954 HS (.000) * (.954) (.000) *

1.633 3.653 0.211 PS×G (.188) (.047) * (.812)

1.359 1.643 1.171 PS×HS (.249) (.207) (.357)

1.393 1.075 2.088 G×HS (.257) (.362) (.153)

0.852 1.906 0.100 PS×G×HS (.565) (.153) (.981)

PS: Pruning Shear, G: Gender, HS: Hand Size (categorized by hand length)

* Significant at the level of p <.05

Figure 4-18: Interaction plot (data means) for subjective satisfaction of grip force requirement by pruning shear and gender.

105

100 88.2 90

60 51.4 50

40 31.3 30

Satisfaction of Grip ForceRequirement[%] Grip of Satisfaction 0 CP RGP TGP Pruning Shear Handle Design

Figure 4-19: Average subjective satisfaction of grip force requirement by pruning shear design.

Figure 4-20: Subjective satisfaction of grip span by gender and hand size.

106

100

90 79.05 80

60 55.68

40 30.12 30

20 Satisfaction of Grip Span [%] Span Grip of Satisfaction 10

0 Small Medium Large Hand Size

Figure 4-21: Average subjective satisfaction of grip span by hand size.

To choose the best-fit predictors for the subjective satisfaction rating of grip span, a linear regression analysis was separately performed for men and women by employing the hand- related anthropometric measures (Table 4-2) as the set of independent variables (Table 4-15 and

4-16). Using stepwise regression model, two equations were developed for men (R2 = 0.493 and p-value = .038) and for women (R2 = 0.976 and p-value = .000)

!!"#$ !"# % = 19.6 !" − 121.6

!!"#$ !"#$% % = 84.9 !"## + 45.6 !"## − 29.6 !" − 39.5(!"##) − 786.653 where SSRGP is the subjective satisfaction rating of grip span, PW is the palm width, RFLL is the ring finger link length, MFLL is the middle finger link length, HL is the hand length, and

IFLL is the index finger link length.

The tolerance and the variance inflation factor value were calculated to check for multicollinearity problems. Based on the recommendations from the literature, any model with a

107 tolerance of 0.4 or less (Allison, 1999) and a variance inflation factor greater than 10 (Kellis et al.,

2000; Neter et al., 1985) has a problem of multicollinearity. No multicollinearity problem was found with our factors in the final equations (Table 4-16).

4.3.5. Muscle Activity

A MANOVA was conducted to examine the effects of Pruning Shear Design, Gender,

Hand Size and their interactions on the dependent measures, standardized EMG (sEMG) values for FDS and ED, collectively. If statistical significance of the MANOVA (p < 0.05 for the Wilks’

Lambda statistic) was found for a main effect (or interaction), then that effect (or interaction) was tested using individual ANOVA for each measure. A randomized complete block design was used in this statistical analysis with “participant” acting as the blocking variable, thereby controlling for the high levels of inter-individual variability.

The MANOVA results of the sEMG values for FDS and ED showed a significant effect of both Gender and Hand Size, but not their interactions (Table 4-14). While the univariate analyses did show some significant effects, there were no consistent trends in these muscle activation profiles that would lead one to conclude that one pruning shear was superior to the others (Figure 4-22). On the other hand, the effects of Gender and Hand Size were more pronounced and formed consistent trends. Based on the sEMG data, the average muscle activities exerted by the participants during pruning constituted about 60.3% of MVC for FDS and 65.8% of MVC for ED (Figure 4-23). Women used approximately 3.5% more FDS and 7.7% more ED than those of men (Figure 4-23). Especially, the large hand-size participants used only about 49 to

53% of MVC for FDS and ED while the small hand-size participants 71 to 80% of their MVC, respectively (Figure 4-24). In terms of medium hand-sized participants, it was interesting to note that women used less FDS than men during pruning (Figure 4-25).

108

Table 4-14: Results of MANOVA and ANOVA for sEMG data for FDS and ED. Each cell is represented as F-statistic (p-value).

Effect MANOVA sEMG (FDS) sEMG (ED)

0.326 0.538 0.665 PS (.859) (.593) (.527)

3.967 1.811 5.270 G (.039) * (.195) (.034) *

9.390 21.026 24.867 HS (.000) * (.000) * (.000) *

0.547 0.193 0.247 PS×G (.702) (.826) (.784)

1.023 0.662 0.492 PS×HS (.438) (.627) (.742)

1.661 3.569 1.717 G×HS (.182) (0.049) * (.208)

0.154 0.086 0.014 PS×G×HS (.995) (.986) (1.000)

PS: Pruning Shear, G: Gender, HS: Hand Size

* Significant at the level of p <.05

Figure 4-22: sEMG of the forearm muscles as a function of Pruning Shear.

109

80 72.4 70 64.7 65.8 59.3 60.3 60 55.8

40 FDS sEMG [%] 30 ED 20

0 Men Women Total Gender

Figure 4-23: sEMG of FDS and ED by gender.

90 79.5 80 70.5 70 65.2 65.8 60.9 60.3 60 52.8 49.3 50

40 FDS sEMG [%] ED 30

0 Small Medium Large Total Hand Size

Figure 4-24: sEMG of FDS and ED by hand size.

110

Figure 4-25: Interaction plot (data means) for sEMG (FDS) by gender and hand size.

To investigate the relationship between muscle activity and hand anthropometric measures, a linear regression analysis was performed by employing the anthropometric measures as the set of independent variables. Using stepwise regression model, four equations were developed for each forearm muscle and for each gender. Using stepwise regression model, the following equations were separately developed for men and women (p < .05).

2 sEMG FDS(men) [%] = 6.3(HL) − 61.9 (R = 0.688)

2 sEMG FDS(women) [%] = −55.9(RFLL) + 13.5(IFLL) + 33.4(PW) + 302.1 (R = 0.922)

2 sEMG ED(men) [%] = 7.3(HL) − 61.9 (R = 0.526)

2 sEMG ED(women) [%] = −68.0(RFLL) + 16.3(IFLL) + 39.8(PW) + 371.3 (R = 0.934)

111 4.3.6. Grip Force Distribution

Total and Individual finger and phalange forces

The individual finger force was defined as the sum of the three phalangeal segment forces for that finger, and the total finger force was defined by the sum of all four-finger forces, from the index to little fingers. A significant gender effect was found with respect to the total and individual finger/phalange forces (Table 4-15 and 4-16). On average, women (156.69 N) exhibited about 91.6% as much as total finger force capability as that of men (170.96 N). The results also indicated that women mainly used their distal phalanges to operate pruning shears while men mainly used their middle phalanges (Figure 4-26). Disregarding the gender, the middle finger was mainly utilized and generated 41.5% and 43.8% of total finger force for men and women, respectively (Figure 4-27). For the index finger, women (17.71 N) exhibited about only

64.5% of force which men (27.47 N) exerted (Figure 4-26). Hand size had also a significant effect on the total and individual phalange forces because women consisted of more medium and small hand-size participants. However, more significant effects were observed with the gender factor. Table 4-17 summarizes individual and total finger and phalange force contributions by gender.

112

Table 4-15: Summary of total and individual finger/phalange forces by gender.

Mean Std. Dev. Std. Error 95% Confidence Interval for Mean Min Max

Lower Bound Upper Bound

Men 65.52 12.70 2.99 59.21 71.84 45.90 90.66 Distal Women 76.00 12.04 2.84 70.01 81.99 55.19 97.96 Phalange Total 70.76 13.30 2.22 66.26 75.26 45.90 97.96

Men 84.43 15.77 3.72 76.59 92.27 52.90 109.70 Middle Women 68.42 15.40 3.63 60.76 76.08 44.10 90.20 Phalange Total 76.43 17.38 2.90 70.55 82.31 44.10 109.70

Men 19.47 5.80 1.37 16.59 22.36 11.04 30.32 Proximal Women 13.81 4.23 1.00 11.70 15.91 7.07 21.01 Phalange Total 16.64 5.77 0.96 14.69 18.59 7.07 30.32

Men 27.47 7.42 1.75 23.78 31.16 12.13 40.37 Index Women 17.71 5.65 1.33 14.90 20.52 5.79 29.23 Finger Total 22.59 8.17 1.36 19.83 25.36 5.79 40.37

Men 71.00 4.81 1.13 68.61 73.39 60.86 78.29 Middle Women 68.67 3.95 0.93 66.71 70.64 63.20 74.02 Finger Total 69.84 4.50 0.75 68.31 71.36 60.86 78.29

Men 58.81 6.90 1.63 55.37 62.24 47.46 67.25 Ring Women 53.13 6.16 1.45 50.07 56.19 42.55 66.87 Finger Total 55.97 7.06 1.18 53.58 58.36 42.55 67.25

Men 13.69 8.98 2.12 9.22 18.15 0.98 34.56 Little Women 17.17 9.09 2.14 12.65 21.70 2.18 33.61 Finger Total 15.43 9.08 1.51 12.36 18.50 0.98 34.56

Men 170.96 15.95 3.76 163.03 178.90 135.92 195.43 Total Women 156.69 12.78 3.01 150.33 163.05 127.08 177.31 Finger Total 163.83 15.98 2.66 158.42 169.23 127.08 195.43

113

20 18 16 14 12 10 Men 8 Women Contact Force [N] 6 Total 4 2 0 Distal Middle Proximal Phalange

Figure 4-26: Total and individual phalange forces by gender.

40 Men Women 30 Contact Force [N] Total 20

0 Index Middle Ring Lile Finger

Figure 4-27: Total and individual finger forces by gender.

114

Table 4-16: One-way ANOVA result for total and individual finger/phalange forces by gender.

Sum of Squares df Mean Square F Sig.

Between Groups 988.16 1 988.16 6.454 0.016 Distal Within Groups 5205.84 34 153.11 Phalange (*) Total 6193.99 35

Between Groups 2305.76 1 2305.76 9.49 0.004 Middle Within Groups 8261.05 34 242.97 Phalange (*) Total 10566.81 35

Between Groups 288.94 1 288.94 11.21 0.002 Proximal Within Groups 876.40 34 25.78 Phalange (*) Total 1165.35 35

Between Groups 857.61 1 857.61 19.704 0.000 Index Within Groups 1479.84 34 43.53 Finger (*) Total 2337.45 35

Between Groups 48.70 1 48.70 2.512 0.122 Middle Within Groups 659.08 34 19.39 Finger Total 707.78 35

Between Groups 289.91 1 289.91 6.78 0.014 Ring Within Groups 1453.83 34 42.76 Finger (*) Total 1743.74 35

Between Groups 109.41 1 109.41 1.34 0.255 Little Within Groups 2776.76 34 81.67 Finger Total 2886.18 35

Between Groups 1833.84 1 1833.84 8.777 0.006 Total Within Groups 7103.72 34 208.93 Finger (*) Total 8937.56 35

* The mean difference is significant at the .05 level.

115

Table 4-17: Total and individual finger and phalange force contributions.

Total Gender Mean individual phalange contributions [%] Mean individual finger contributions [%] Finger Force [N] Distal Middle Proximal Index Middle Ring Little

Men 170.96 0.39 0.50 0.11 0.16 0.42 0.34 0.08

Women 156.96 0.48 0.43 0.09 0.11 0.44 0.34 0.11

Total 163.83 0.44 0.46 0.10 0.14 0.43 0.34 0.09

Grip force balance between finger forces and palm forces

The total palm force was defined by the sum of opposite directional forces to the finger force from thenar, groove, and hypothenar regions. The finger/palm force balance (fpBalance) was calculated by the ratio between total finger force and total palm force. ANOVA analysis revealed a significant pruning shear design effect on the fpBalance (Table 4-18 and 4-19 and

Figure 4-28). On average, pruning with CP exhibited the least fpBalance (0.66) which caused a large amount of excessive force on the palm side. The fpBalance was significantly improved with

TGP (0.92) and moderately improved with RGP (0.80) (Figure 4-29).

116

Table 4-18: Summary of total finger/palm force and balance by pruning shear design.

Mean Std. Dev. Std. Error 95% Confidence Interval for Mean Min Max

Lower Bound Upper Bound

CP 151.42 14.86 4.29 141.98 160.86 127.08 175.86

Total RGP 169.40 11.24 3.24 162.26 176.53 145.57 180.25 Finger Force TGP 170.67 14.59 4.21 161.40 179.93 150.71 195.43 Total 163.83 15.98 2.66 158.42 169.23 127.08 195.43

CP 230.13 26.91 7.77 213.03 247.23 184.93 270.30

Total RGP 213.44 18.95 5.47 201.39 225.48 179.09 234.89 Palm Force TGP 185.91 19.28 5.57 173.66 198.16 152.38 224.90 Total 209.83 28.27 4.71 200.26 219.39 152.38 270.30

CP 0.66 0.04 0.01 0.64 0.68 0.59 0.72

Finger/Palm RGP 0.80 0.03 0.01 0.77 0.82 0.75 0.85 Force Balance TGP 0.92 0.06 0.02 0.88 0.96 0.85 1.03 Total 0.79 0.12 0.02 0.75 0.83 0.59 1.03

250

200

150

Fingers 100 Palm Conctat Force [N]

0 CP RGP TGP Pruning Shear Design

Figure 4-28: Total finger/palm forces by pruning shear design.

117

1.0

0.9

0.8

0.7

0.6

0.5

0.4

Finger/Palm Force Balance 0.3

0.2

0.1

0.0 CP RGP TGP Pruning Shear Design

Figure 4-29: fpBalance data by pruning shear design.

Table 4-19: One-way ANOVA result for total finger/palm force and balance by pruning shear design.

Sum of Squares df Mean Square F Sig.

Between Groups 2780.22 2 1390.11 7.450 0.002 Total Finger Within Groups 6157.34 33 186.59 Force Total 8937.56 35

Between Groups 11967.22 2 5983.61 12.335 0.000 Total Palm Within Groups 16008.13 33 485.10 Force Total 27975.35 35

Between Groups 0.41 2 0.21 102.346 0.000 Finger/Palm Force Within Groups 0.07 33 0.00 Balance Total 0.48 35

118 4.3.7. Wrist Deviations in F/E and U/R

Participants always held the pruning shears in their dominant hand using a power grip.

They rarely gripped the pruning shears with both hands to cut the wooden dowels. ANOVA analysis on the wrist deviation data during pruning indicated that both pruning shear design and gender are significant factors for the wrist deviations in U/R (Table 4-20, 4-21, 4-22, and 4-23).

On average, the wrist was more often bent in extension (15.94°) and ulnar (7.70°) than in flexion

(6.37°) and radial (3.46°) directions. For both genders, pruning with TGP performed many cuts with the least extension deviation (11.50°) on the wrist and pruning with RGP performed them with the least ulnar deviation (5.85°) on wrist. Hand size had also a significant effect on the wrist deviations in U/R. The observations, however, were more pronounced with the gender factor.

Table 4-20: Summary of wrist deviation in F/E and U/R by pruning shear design.

Mean Std. Dev. Std. Error 95% Confidence Interval for Mean Min Max Lower Bound Upper Bound CP 6.12 3.89 1.12 3.65 8.60 0.75 11.37

RGP 5.68 3.30 0.95 3.58 7.77 0.74 11.15 Flexion TGP 7.30 3.61 1.04 5.01 9.60 1.59 12.27

Total 6.37 3.57 0.60 5.16 7.58 0.74 12.27

CP 21.86 11.29 3.26 14.69 29.04 6.61 36.82

RGP 14.46 10.00 2.89 8.10 20.81 0.94 25.61 Extension TGP 11.50 8.23 2.38 6.27 16.73 0.23 22.34

Total 15.94 10.60 1.77 12.35 19.53 0.23 36.82

CP 10.44 2.85 0.82 8.63 12.26 3.65 14.52

RGP 5.85 4.03 1.16 3.29 8.41 0.09 13.83 Ulnar TGP 6.83 2.50 0.72 5.24 8.41 3.34 12.15

Total 7.70 3.69 0.62 6.46 8.95 0.09 14.52

CP 3.39 1.44 0.41 2.47 4.30 0.89 5.74

RGP 3.29 1.84 0.53 2.12 4.46 0.09 6.26 Radial TGP 3.70 1.84 0.53 2.53 4.87 0.39 6.12 Total 3.46 1.68 0.28 2.89 4.03 0.09 6.26

119

Table 4-21: One-way ANOVA result for wrist deviations in F/E and U/R by pruning shear design.

Sum of Squares df Mean Square F Sig.

Between Groups 16.89 2 8.44 0.648 0.530

Flexion Within Groups 430.13 33 13.03

Total 447.02 35

Between Groups 684.44 2 342.22 3.478 0.043

Extension Within Groups 3247.34 33 98.40

Total 3931.78 35

Between Groups 140.68 2 70.34 6.891 0.003

Ulnar Within Groups 336.84 33 10.21

Total 477.51 35

Between Groups 1.14 2 0.57 0.193 0.826

Radial Within Groups 97.24 33 2.95

Total 98.38 35

Table 4-22: Summary of wrist deviations in F/E and U/R by gender.

Mean Std. Dev. Std. Error 95% Confidence Interval for Mean Minimum Maximum

Lower Bound Upper Bound

Men 5.95 3.85 0.91 4.04 7.87 0.74 12.27

Flexion Women 6.78 3.33 0.78 5.13 8.44 1.48 11.18

Total 6.37 3.57 0.60 5.16 7.58 0.74 12.27

Men 9.36 7.89 1.86 5.43 13.28 0.23 27.33

Extension Women 22.52 8.79 2.07 18.15 26.89 5.14 36.82

Total 15.94 10.60 1.77 12.35 19.53 0.23 36.82

Men 5.55 3.34 0.79 3.88 7.21 0.09 10.98

Ulnar Women 9.86 2.65 0.63 8.55 11.18 6.36 14.52

Total 7.70 3.69 0.62 6.46 8.95 0.09 14.52

Men 3.03 1.72 0.41 2.17 3.88 0.09 6.12

Radial Women 3.89 1.56 0.37 3.12 4.67 0.39 6.26

Total 3.46 1.68 0.28 2.89 4.03 0.09 6.26

120

Table 4-23: One-way ANOVA result for wrist deviations in F/E and U/R by gender.

Sum of Squares df Mean Square F Sig.

Between Groups 6.17 1 6.17 0.476 0.495

Flexion Within Groups 440.85 34 12.97

Total 447.02 35

Between Groups 1559.84 1 1559.84 22.359 0.000

Extension Within Groups 2371.93 34 69.76

Total 3931.78 35

Between Groups 167.89 1 167.89 18.437 0.000

Ulnar Within Groups 309.62 34 9.11

Total 477.51 35

Between Groups 6.72 1 6.72 2.493 0.124

Radial Within Groups 91.66 34 2.70

Total 98.38 35

4.4. DISCUSSION

In the present study, a modified functional digit link length, which reflects actual grip spans for each finger, was defined and employed. For the design of pruning shears, most critical hand anthropometric measurements were hand length and palm width for men in terms of grip strength, contact force, subjective discomfort and satisfaction and muscle usage. This finding was supported by previous studies using the two measures as important parameters for biomechanical hand models (e.g., Hall, 1997; Lin et al., 2001; Sancho-Bru et al., 2003; Wimer et al., 2009). For women, however, index, middle, and ring finger link lengths were additionally selected as bets-fit predictors for their operating patterns. This indicates that women tend to use more various types of fingers and muscles to overcome their less grip strength to operating pruning shears. In this reason, the modified functional digit link length should be carefully considered when designing a pruning shear for women users.

121 The best single measurement to predict maximum grip strength was the palm width for both genders. A greater palm width suggests that an individual has larger muscles and bones, but greater palm width also provides an advantage in gripping. Gripping the dynamometer further down the handle provides a mechanical advantage by lengthening the moment arm of the resultant grip force vector, thereby producing a greater reading with application of the same force.

Because all individuals were required to grip the dynamometer with their all four fingers and the palm at a fixed grip span, 8 cm, individuals with wider palms are able to generate slightly better leverage on the dynamometer. The variables with weak but positive correlation to grip strength were finger link length, finger length, and hand length that vary more independently from overall body size than do the other measurements of the hand and forearm. Because the fingers have no intrinsic muscle mass, longer fingers do not necessarily indicate greater overall strength, and may reduce mechanical efficiency. Other than anthropometric measures, gender, hand size, and pruning shear design were main factors used for entire analyses in this study. For many cases, it was observed that the hand size effect was strongly related to the gender factor.

For the relationship between grip strength and contact force, average total contact force was 2.3 times greater than average Jamar grip strength. The strong relationship was best described with a linear regression model (R2 = 72.2%, Std. Error = 30.15) in Section 4.3.3. Thus, contact force is relevant to estimate grip force for tasks involving squeezing parallel bars and diagonal cross-action tools such as pruning shears and wire cutters.

The evaluation of subjective hand discomfort ratings indicated that participants mostly preferred RGP due to the rubber-padded grip to minimize pressures on the critical hand regions, thumb, thenar, fingers, metacarpals, and wrist. Participants rated TGP as relatively more discomfort than RGP because the thumb grip occurred a pain on the thumb phalanges while exerting force to cut. The result also indicated that pruning with CP involved significantly high discomfort in most of hand regions which were investigated in this study. The evaluation of

122 subjective design satisfaction ratings indicated that TGP was the most satisfactory in terms of grip force requirement. From the participant comments, it was observed that pruning with CP did not provide the sense of grip security while pruning. This may be a possible explanation for the least satisfaction level with CP from most of participants. The grip span was not much satisfied except for the large hand-size participants. The result of subjective ratings indicates that the combination of two design features, rubber-padded grip and thumb grip, as well as providing adjustability of grip span between the two handles based on user’s hand size may be the most contributory factors to maximize the satisfaction levels from users. It was interesting to note that women’s perception on any new design features has much more significant effect on the subjective ratings such as hand discomfort and design satisfaction than men although women’s physiological measurements after using that tool were not that good. Moreover, women were much more sensitive for pains and discomfort than men even for an identical pruning shear. This might be from the fact that women’s pressure-pain thresholds are relatively higher than those of men, especially for finger and thenar regions as Hall (1977) reported.

The muscle activities of the flexor (FDS) and extensor (ED) were measured to investigate any significant effects of pruning shear design, gender, and hand size on sEMG values. There were significant differences between genders and hand sizes although there were no consistent trends in these muscle activation profiles that would lead one to conclude that one pruning shear was superior to the others. The two newly designed pruning shears, RGP and TGP, were focused on the design feature of handgrip shape to support grip force distribution and gripping posture of the hand. Other than the handgrip shape, most of design features were remained same such as grip span, lower handle shape, and blade coating material. This might cause the pruning shear design had no effect on the muscle activities. The muscle activity data analysis showed that women consistently used more FDS and ED than those of men while any types of pruning shears. This is also supported by the relationship between muscle activity and

123 hand anthropometric measures. Women adopted more various fingers such as index, middle, ring, and even the weakest little finger to operating pruning shears while men used a few primary fingers such as middle and ring finger.

The analyses of grip force distribution over the hand found that women mainly use their distal phalanges to operate pruning shears while men mainly use their middle phalanges. This indicates that the pruning shear might be inappropriately designed for women in terms of its too large grip span. If the force continues to be applied at the distal phalanges during work, the weaker flexor muscle, the flexor digitorum profundus, becomes the primary flexor. Sanders

(2004) reported that the tendon force is two to three times greater than when forces are applied at the distal phalanges than when forces are applied at the middle phalanges. A large handle opening also places excess stress on the collateral ligaments of the thumb carpometacarpal and metacarpophalangeal joints.

For the force balance between fingers and palm, pruning with CP exhibited the least balance (0.66) which caused a large amount of excessive force on the palm side while the balance was significantly improved with TGP (0.92) and moderately improved with RGP (0.80). In terms of TGP, users are able to grip the attached thumb grip by their thumb finger and this helps thumb finger involvement in power grip motion by inserting its force to the same direction of other four fingers (Figure 4-30). For RGP, the wider rubber-padded upper handle allows a firm and secure grip for the thumb finger and the thenar area. In turn, this prevents other four fingers from excessive rotating around the lower handle. In this reason the force direction of the four fingers doesn’t change too much during the operation (Figure 4-31). Fransson-Hall and Kilbom (1993) found that the most sensitive areas on the hand to be thenar region and excessive external pressure on this area could cause severe pain due to the low pressure-pain threshold and finally place the users at risk of CTS. This finding supports the importance of grip force distribution to maximize fpBalance in the design of diagonal cutting hand tools.

124

Figure 4-30: Improved fpBalance while operating TGP.

Figure 4-31: Improved fpBalance while operating RGP.

Figure 4-32 summarizes the gender-specific operating pattern investigated in this study.

The example sEMG plots are timely synchronized with wrist deviation data which were obtained

125 from large hand-size men and small/medium hand-sized women participants while both of them were using the conventional pruning shears. Women participants, relatively having small hand dimensions, used more FDS muscle to close handles as well as more ED muscle to extend their finger joints to reach the lower handle of pruning shear. This gender-specific operating pattern was consistently observed through the rest of participants.

For large hand-sized men, they take much shorter cutting time with less peak force of

FDS. However, small/medium hand-sized women take much longer cutting time and more frequent ED muscle use and finally a large excessive peak force of FDS is generated. That means women continuously try to securely grip the lower handle due to relatively larger grip span than their finger lengths. And also, to compensate their less grip strengths, an excessive squeezing force is generated by fully flexing her finger joints as possible as they could. The women’s operating pattern involved in significantly large amount of wrist extension to generate full flexion of finger joints as well as large excessive forces to reach the static isometric contraction status at the final stage of cutting.

126

Figure 4-32: An example of sEMG plots with wrist deviation obtained from large hand sized men and small/medium hand-sized women participants.

127

Chapter 5

CONCLUSIONS

It is evident that when hand tools have to be used during farming and gardening tasks that potentially involve biomechanical risk factors that may contribute to or aggravate a musculoskeletal disorder (MSD). Although women population is increasing and interesting subset of farming and gardening in U.S., their anthropometry and tool operating patterns may not fit many jobs and tasks designed originally for the average male. To solve this problem, women have driven the need to develop more ergonomic features for the tools frequently used by both genders by paying more for increased ease and less discomfort. From the two case studies, it was found that women’s perception on any new design features has much more significant effect on the subjective ratings or evaluations such as hand discomfort and design satisfaction than men although women’s physiological measurements after using the tools were not that good.

Moreover, women were much more sensitive for pains and discomfort than men even for an identical hand tool use. In addition, women overcome their biomechanical disadvantages by employing more various muscles and body parts while operating hand tools.

For the purpose of designing appropriate hand tools for women, this study presents two case studies for shovels and pruning shears that have been prioritized to be immediately redesigned by active women farmers, gardeners, and market growers.

Case study 1:

• Introduced a redesigned shovel with key ergonomic design parameters (the

combination of 36° lift angle, use of second handle, and elongated D handle) and

less energy cost as well as more upright posture while shoveling and lifting soil.

• Developed a design process including women user preference component in

128 terms of the preferred handle height (1145 mm), which are capable to

accommodate much larger women population than traditional anthropometric

methods, for the new prototype of shovel with bi-functional gooseneck blade.

• Identified women’s operating strategies (knee flexion with flat back) to overcome

their biomechanical disadvantages due to body size during shoveling work.

Gender-specific operating patterns were observed during shoveling work. Greater knee flexion, utilized by women, could reduce the degree of trunk flexion while lifting soil and also lower the center of gravity of the body for a postural stability at the same time. As opposed to women, men performed the shoveling tasks with large trunk flexion and flat knees, which is similar to a squat lifting. This strategy may be due to the relatively greater back strength found in men. In addition, this strategy could save working time for men while shifting from lifting the load to moving it.

Case study 2:

• Determined the most critical hand anthropometric measures (hand length, palm

width, and digit link length) affecting grip span, contact force, subjective

discomfort and satisfaction rating, and muscle activation.

• Designed new pruning shears with rubber-padded grip and thumb grip to

minimize pressures on the critical hand regions and to improve muscle activities,

grip force distribution, and wrist deviations.

• Identified women’s operating strategies (a large degree of wrist extension, use of

more ED muscle, and excessive squeezing force) to overcome their

biomechanical disadvantages due to hand size during pruning work.

For the gender-specific operating patterns during pruning work, it is concluded that women having medium or small hand sizes use their ED muscles more frequently than men having medium or large hand sizes as the muscle activity of FDS reaches its peak. This is because

129 women try to grip the lower handle firmly in order to acquire a large magnitude of cutting force due to relatively shorter hand length and less grip strength. In addition, women seem to compensate their decreased grip strength by taking a longer cutting period. During this period, women are generating a greater relative squeezing force as compared to men. In addition, women showed significantly greater wrist extension so as to generate full flexion of the finger joints.

The newly designed model, RGP, which is equipped with a padded upper handle, can minimize the force localization on the thenar region by maximizing the contact area between the handle surface and the palm side of thenar/hypothenar regions. The TGP, which is equipped with a thumb support that is placed just beyond the existing grip guard, provides a guard to prevent the thumb finger from slipping during work. These features of TGP provide users with more efficient grip by involving the thumb, which remains passive with in the conventional pruning shears.

Despite the importance of designing hand tools for women, few studies have identified gender specific operating patterns. Most studies have focused on evaluating hand tools based on existing ergonomic guidelines without investigating potential gender-specific operating behaviors.

Unique features that differentiate this study from previous studies are the comprehensive understandings of the relationship between user preference and intended biomechanical advantages in hand tool design.

(1) User preference without intended biomechanical advantages may

a. Promote better subjective satisfaction levels, but may not improve task efficiency

and performance. This was observed in the shovel study (Phase II), which

investigated the effects of fixed second handle position and preferred second

handle position.

b. Cause another anthropometric mismatch, which can produce user’s

dissatisfaction. This was observed from the shovel study (Phase I) in the final

prototype length was still shorter for the women users.

130 (2) User preference with intended biomechanical advantages can

a. Increase the task performance and improve physiological responses, but may not

improve postural comfort. This was observed from the shovel study (Phase II),

which investigated the effects of biomechanically balanced second handle

position and user’s preferred position and from the pruning shear study, which

investigated subjective discomfort level on the thumb finger while operating TGP.

The main contributions from this ergonomic design study are more comprehensive information for the hand tool design that truly provides a better fit of jobs, tasks, and tools to users. These important design factors and gender-specific operating patterns can be applied in different settings to both long- and short-handled hand tools. As a result of the present research more ergonomic and usable bi-functional gooseneck shovel was supplied to women in the U.S. gardening market.

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148 VITA

Jesun Hwang

Jesun Hwang earned a Bachelor of Science degree in Industrial Engineering at Inha

University, South Korea in 2003. In 2005, he was awarded a Master of Science degree in

Industrial Engineering from Inha University, South Korea. In 2011, he received a Doctor of

Philosophy degree in Industrial Engineering with Human Factors option from The Pennsylvania

State University. His research interests focus on (1) implementing human-centered research for

UI/UX/HMI design for hand tools, (2) measuring human sensory response data such as touch, pressure, vision, and sound, (3) modeling user’s objective and subjective preference to identify customer needs for usability effect and affordance, (4) optimizing anthropometric comforts, functional requirements, and physical specifications for devices or products, (5) developing representative human models for anthropometric design, (6) simulating and analyzing human motions while using devices, and (7) determining depth of processing in design contexts based on human information process where recall and retention of information is important.