The Impact of the Auditory and Visual Environments on Balance in Children with Bilateral Vestibular Loss and Cochlear Implantation

Home , Flocculonodular lobe

Nikolaus Ernst Wolter

A thesis submitted in conformity with the requirements for the degree of Master of Science Institute of Medical Sciences University of Toronto

The Impact of the Auditory and Visual Environments on Balance in Children with Bilateral Vestibular Loss and Cochlear Implantation

Nikolaus Ernst Wolter

Master of Science

Institute of Medical Sciences University of Toronto

2014 Abstract

Vestibular impairment is common in congenital sensorineural hearing loss yet children are remarkably able to remain upright. To understanding how these children compensate for their bilateral cochelovestibular loss (BVL) we investigated the effects visual and auditory virtual environments in children with BVL and bilateral cochlear implantation (CI), ages 8.5-17.9 years on balance. Children with BVL had significantly impaired balance compared to typically developing children. Body movement was greater in children with BVL balancing. Children with

BVL relied on vision to a greater extent than their typically developing peers. Moving objects in the environment did not alter balance in either group. Balance and postural control improved in children with BVL when CI were on. Children with BVL rely on vision and auditory input through CI in order to balance but this does not restore balance to normal levels. Novel methods are required to reestablish vestibular-type input in this vulnerable population.

Acknowledgments

The completion of this work has depended on the support, guidance and kindness of a tremendous number of people. I cannot adequately express the debt of gratitude I have to all of you for your countless hours of support. Please accept my sincerest thanks with a special thank you to:

My research supervisor, Dr Karen Gordon, for guiding me through this process, for making me a more critical thinker, and helping to establish the foundation I will use to continue to answering my many questions for the rest of my career. Thank you to Salima, Melissa, Stephanie and Morrison. I expected to meet a number of highly intelligent people during the pursuit of my Masters degree but I did not expect to meet such genuinely good and kind people and to make such good friends.

My clinical supervisors, Dr Blake Papsin and Dr Sharon Cushing, it is not easy to express the debt of gratitude I owe you both. Dr Papsin, thank you for inspiring me to do this and pushing me to make more of myself than I ever thought possible. Dr Cushing, I could not have done this without you, thank you for your tireless support and encouragement and for being behind me every step of the way. You have both been incredible mentors and role models and you are both examples of the kind of surgeon and scientists I aspire to be.

The TRI CEAL and iDAPT team, thank you Dr Campos for your patience, guidance, and kind words. You have been an amazing source of information, advice and support and I feel very fortunate to have met you. Thank you also to your team: Susan, Alison, and Bruce. Without their support none of this work would have been possible.

My family, thank you to my mother and father for their encouragement and kind words throughout my education. Finally, thank you to my wife, Jennifer. You have been the source of all the good that I have done since I first met you. Thank you for making me better, for picking me up, dusting me off and pushing me back into the ring. Thank you for everything.O.

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Table of Contents

Acknowledgments...... iii Table of Contents ...... iv List of Tables ...... vii List of Figures ...... viii List of Appendices ...... x List of Abbreviations...... xi Chapter 1...... 1 1 Introduction...... 1 1.1 Research Questions ...... 1 1.2 Background ...... 2 1.3 Research Objectives ...... 6 1.4 Anatomy and Physiology of the Peripheral Vestibular System ...... 7 1.4.1 Vestibular Reflex Pathways...... 11 1.5 Integration of Vestibular Information ...... 14 1.6 Development of Postural Control ...... 16 1.7 Methods of Assessment of Balance Function in Children ...... 20 1.7.1 Posturography...... 21 1.7.2 Imaging Measurement Techniques...... 21 1.7.3 Assessment of Balance and Motor Control in Children ...... 23 1.8 Assessment of Balance in Real-World Environments...... 24 1.9 Cochlear Implantation and Vestibular Function ...... 26 1.10 Balance in Children with BVL and Bilateral Cochlear Implants...... 29 1.11 Summary...... 32

Chapter 2...... 34 2 Methods ...... 34 2.1 Overview...... 34 2.2 Participants ...... 34 2.3 Subjective Assessment of Static and Dynamic Balance Function: BOT-2 Balance Subtest ... 36

2.4 Objective Methods of Static and Dynamic Balance Function ...... 37 2.4.1 Motion Capture Analysis...... 37 2.4.2 Force plate Posturography...... 38 2.5 Stimulus Environment: Street Lab Visual Dome ...... 41 2.6 Testing Protocol...... 42 2.7 Data and Analysis ...... 44

Chapter 3...... 47 3 Results...... 47 3.1 Validity and Reliability of BOT-2: Balance Subtest in Detecting Balance Dysfunction in Children...... 47 3.1.1 Inter-Rater Reliability ...... 47 3.1.2 Known Group Validity ...... 48 3.1.3 Convergence Validity ...... 52 3.2 Impact of Vision on Balance in Children with BVL ...... 68 3.2.1 Does Vision Play a Greater than Normal Role in Balance in Children with Bilateral Cochleovestibular Loss than their Typically developing Peers?...... 68 3.2.2 Does the Visual Environment Affect Balance in Children?...... 76 3.3 The Impact of Audition on Balance in Children with BVL...... 82 3.3.1 Impact of Restoration of Hearing Through Bilateral Cochlear Implantation on Balance..... 82 3.3.2 Impact of Directional Sound Cues on Balance in Children ...... 88

Chapter 4...... 100 4 Discussion...... 100 4.1 Is the BOT-2 Balance Subtest a Valid and Reliable Measure of Balance in Children?...... 101 4.2 Does Vision Play a Greater than Normal Role in Balance in Children with Bilateral Cochleovestibular Loss than their Typically developing Peers?...... 108 4.3 Does the Visual Environment Affect Balance in Children? ...... 111 4.4 Can Balance Be Restored in Children with Bilateral Cochleovestibular Loss Through Bilateral Cochlear Implantation?...... 114 4.5 Does the Presence of Directional Sound Cues in the Environment Allow Better Balance than a Directionless Sound Environment?...... 116 4.6 Necessity of Restoring Head Referenced Sensory Information in Children with Cochleovestibular Loss...... 119

4.7 Future Directions...... 121

Chapter 5...... 124 5 Conclusions...... 124 Chapter 6...... 126 6 References...... 126 Appendices...... 134

List of Tables

Table 2.1 Demographic factors for both Children with BVL who use CI and typically developing children Table 2.2 Cochlear Implant user demographic data Table 2.3 BOT-2 Task Summary and grading scheme Table 2.4 Sensory conditions for typically developing children Table 2.5 Sensory conditions for children with BVL Table 3.1 Inter-rater reliability Table 3.2 Known group validity results for two-footed tasks Table 3.3 Known group validity results for one-footed tasks Table 3.4 Time to fall comparison between implant on and implant off Table 3.5 Time to fall comparisons between the typically developing children and children with BVL in two sound environments Table 3.6 Postural stability compared by COP rms between the typically developing children and children with BVL in two sound environments Table 3.7 Postural stability compared by COP velocity between the typically developing children and children with BVL in two sound environments Table 3.8 Head pitch angle rms comparisons between typically developing children and children with BVL standing on one foot in two sound environments

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List of Figures

Section 1 Figure 1.1 The semicircular canals work in functional pairs Figure 1.2 The vestibulo-ocular reflex pathway Figure 1.3 Segmental analysis of the human body Figure 1.4 Methods of testing in virtual environments Section 2 Figure 2.1 Task difficulty defined by the proportion of successful participants Figure 2.2 Position of LED motion capture markers at the head, trunk, and limb positions Figure 2.3 The CEAL Street Lab environment Figure 2.4 Street Lab visual environment Figure 2.5 The 95% confidence ellipse between a typically developed child and their age and gender matched peer with BVL Section 3 Figure 3.1 BOT-2 scaled score results Figure 3.2 Correlation of BOT-2 scores with posturographic measures for task 3 Figure 3.3 Correlation of BOT-2 scores with posturographic measures for task 9 Figure 3.4 Correlations between individual time to fall and posturographic measures Figure 3.5 Correlation between trunk movement and time to fall for task 6 Figure 3.6 Actual age and equivalent balance age Figure 3.7 COP rms compared between typically developing children and children with BVL Figure 3.8 COP rms compared between typically developing children and children with BVL who did not fall Figure 3.9 COP velocity compared between typically developing children and children with BVL who did not fall Figure 3.10 Comparison of head and body movement for two foot tasks Figure 3.11 Comparison of head and body movement for one-footed tasks Figure 3.12 Impact of vision on the duration of stance Figure 3.13 Impact of vision on postural control Figure 3.14 Impact of vision on maximum head angles Figure 3.15 Impact of vision on head angle rms Figure 3.16 Impact of vision on trunk roll Figure 3.17 Impact of vision on trunk pitch Figure 3.18 BOT-2 scores compared between visual environments Figure 3.19 Impact of visual environment on time to fall in eyes open tasks Figure 3.20 Impact of visual environment on postural control in eyes open tasks Figure 3.21 Impact of visual environment on head and trunk movement in children with BVL who use CI Figure 3.22 Impact of visual environment on head and trunk movement in typically developing children Figure 3.23 BOT-2 scaled scored improves when implants are turned on

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Figure 3.24 Balance improvements with CI on Figure 3.25 Impact of auditory input through CI on postural control Figure 3.26 Impact of auditory input through CI on head and trunk pitch Figure 3.27 Impact of auditory input through CI on head and trunk roll Figure 3.28 Balance measured by the BOT-2 was not affected by the presence or absence of directional cues in the sound environment in either typically developing children or children with BVL who use CI Figure 3.29 The type of auditory input does not alter time to fall Figure 3.30 COP rms is not altered by the presence of absence of auditory cues in the environment for either typically developing children or children with BVL who use CI Figure 3.31 Postural stability measured by COP velocity was improved in the presence of directional cues in both children with BVL and typically developed children Figure 3.32 Head pitch angle was increased in typically developed children but not in children with BVL in the presence of spatial auditory cues Figure 3.33 Head roll angles were not significantly altered by environmental sounds in either group Figure 3.34 Trunk pitch angles were significantly increased by environmental sounds in typically developing children Figure 3.35 Trunk roll angles were significantly increased by environmental sounds in Children with BVL standing on two feet

List of Appendices

A.1 Individual Vestibular Testing Results for each participant in the children with BVL group A.2 Task 1 multitrait-multimethod matrix for typically developing children A.3 Task 3 multitrait-multimethod matrix for typically developing children A.4 Task 4 multitrait-multimethod matrix for typically developing children A.5 Task 6 multitrait-multimethod matrix for typically developing children A.6 Task 7 multitrait-multimethod matrix for typically developing children A.7 Task 8 multitrait-multimethod matrix for typically developing children A.8 Task 9 multitrait-multimethod matrix for typically developing children A.9 Task 1 multitrait-multimethod matrix for children with BVL A.10 Task 3 multitrait-multimethod matrix for children with BVL A.11 Task 4 multitrait-multimethod matrix for children with BVL A.12 Task 6 multitrait-multimethod matrix for children with BVL A.13 Task 7 multitrait-multimethod matrix for children with BVL A.14 Task 8 multitrait-multimethod matrix for children with BVL A.15 Task 9 multitrait-multimethod matrix for children with BVL

List of Abbreviations

BVL Bilateral Cochleovestibular Loss CAVE Cave Automatic Virtual Environment CDP Computerized Dynamic Posturography CE Confidence Ellipse CI Cochlear Implants CNS Central Nervous System CNT Could Not Test COM Centre of Mass COP Centre of Pressure HP Head Pitch HR Head Roll IVN Inferior Vestibular Nerve KTK Köperkoordinationstest für Kinder (Body Coordination Test for Children) LED Light Emitting Diode LR Lateral Rectus M-ABC Movement Assessment Battery for Children mCTSIB modified Clinical Test of Sensory Interaction on Balance MR Medial Rectus RMS Root Mean Square SCC Semicircular Canal SE Sound Environment SNHL Sensorineural Hearing Loss SOT Sensory Organization Test SVN Superior Vestibular Nerve TD Typically Developing TP Trunk Pitch TR Trunk Roll VCR Vestibulocollic Reflex VE Visual Environment VEMP Vestibular Evoked Myogenic Potentials VN Vestibular Nucleus VOR Vestibulo-ocular Reflex VSR Vestibulospinal Tract

Chapter 1

1 Introduction

1.1 Research Questions

It is remarkable how well most children keep their balance in a playground. As they swing and climb, they are learning to integrate multiple sensory inputs to maintain a stable percept of the dynamic world around them. Any decrement in sensory input could thus have a significantly debilitating impact on a child’s ability to balance. We propose to examine this issue in a group of children who are deaf and use bilateral cochlear implants as up to 70% of these children have significant peripheral vestibular dysfunction (Buchman, Joy, Hodges, Telischi, & Balkany, 2004; Cushing, Papsin, Rutka, James, & Gordon, 2008; Selz, Girardi, Konrad, & Hughes, 1996). In the current study we have chosen to focus on children with vestibular dysfunction (i.e. no vestibular input) as opposed to children with vestibular hypofunction where some vestibular input may remain as seen in benign positional paroxysmal vertigo, superior canal dehiscence, or Meniere’s disease.

In the following work we intend to answer the following questions:

1) Is the Bruininks Oseretsky Test of motor proficiency - balance subtest a valid and reliable measure of balance? 2) Does visual input play a greater than normal role for children with BVL to balance and will this be affected by the presence of moving objects in the visual environment? 3) A. Are children with known cochleovestibular dysfunction able to compensate for balance problems using hearing restored through bilateral cochlear implants? B. Will different kinds of sound (directional vs. non-directional) impact balance differently?

Children with bilateral cochleovestibular loss (BVL) who use bilateral cochlear implants (CI) have been shown to have impaired static and dynamic balance when tested using the balance subtest of the Bruininks-Oseretsky Test of motor proficiency 2 (BOT-2) (Cushing, Chia, James, Papsin, & Gordon, 2008). For the remainder of the text, children with BVL will refer specifically to our study population of children who had both BVL and bilateral CI. Despite loss of such

important sensory end organs children with BVL eventually meet their motor milestones and manage to participate in normal daily activities, and even perform complex balance tasks such running and even riding a bicycle. Therefore, determining if the balance deficits suggested by BOT-2 testing correlate with quantifiable measures of postural instability and can detect even subtle body segment movements that are involved in balance. These insights may provide clinicians with a more in depth understanding of the balance deficits represented by a given BOT-2 score. Considering the range of activities carried out by patients with BVL, it stands to reason that these children are using other sensory inputs such as vision to compensate for their balance dysfunction. Moreover, children with BVL who receive bilateral CI also have access to spatial sound information that could impact balance. Although the BOT-2 is a reliable clinical tool, it provides only a single, global score and was not designed detect subtle alterations in movement that can impact upright stance. In addition, clinical tools such as the BOT-2 manipulate sensory inputs that are important for balance. They do not themselves; however, comment on the importance of these inputs specifically in a way that can help understand their impact on balance and how children compensate for bilateral vestibular loss (Hatzitaki, Zisi, Kollias, & Kioumourtzoglou, 2002). In this study we use the BOT-2 as a framework and combine it with quantifiable methods of measuring movement and postural stability such as force plates and motion capture to help elucidate the impact of these two sensory inputs on balance in children with BVL. By answering these questions we will gain better insight into the compensatory mechanisms employed by these children, which could potentially yield useful clinical targets for rehabilitation.

1.2 Background

Bipedal stance is a precarious endeavor. By standing up on two feet, humans have positioned their delicate brains on top of a series of body segments that are loosely connected by highly mobile joints. This can be likened to resting a precious Ming vase on the deck of a rolling ship. In order to carry out this careful balancing act, humans must develop a sense of verticality that is accomplished largely by comparison of external objects in the environment with internal representations of the human body. However, as we navigate through our complicated environments this information can often be missing when vision is impaired or may be in conflict with somatosensory input. By sensing gravity, the vestibular system establishes an

external reference that is independent of environmental objects and our body position (Gaertner, Bucci, Obeid, & Wiener-Vacher, 2013; Nashner, Black, & Wall, 1982). In this way it can serve to settle intersensory disputes, which is critical in order to remain upright (O'Reilly, Mortlet, & Cushing, 2013).

The high incidence of vestibular dysfunction in children who are deaf likely reflects the anatomical and physiological similarities between the cochlear and vestibular organs and implies a link between the processes (i.e. genetic mutation, infection etc.) leading to dysfunction of the cochlear and vestibular portions of the inner ear. At the anatomic and physiologic levels, the systems differ in organization of the functional units (hair cells), the overlying layer (basilar membrane vs. otoconia), and the stimulus that leads to system activation. In the cochlea, sound stimulus induces perturbation of the basilar membrane causing deflections of stereocilia on inner hair cells, whereas rotational or translational movements of the head lead to stimulation of hair cells within the semicircular canals and otoconial organs respectively. Given the off-axis position of otoconial end organs they are also able to sense gravitational and translation accelerations during head rotation as a result of centripetal acceleration.

Unlike the other senses, during normal function the vestibular system has no readily recognizable conscious representation, yet it is critical for us to stay standing on two feet and navigate through our environment. Anyone who experiences even a slight imbalance of his or her vestibular output will quickly understand the magnitude of this sense. Acute, unilateral dysfunction of the vestibular system can induce potent hallucinations of movement (known as vertigo) and incapacitating nausea and unsteadiness resulting from an imbalance of vestibular inputs that are interpreted as movement of the head. Interestingly, acute episodes of bilateral vestibular loss that may occur after viral infection or ingestion of a vestibulotoxic medication, such as gentamycin or cisplatin results in different yet disabling symptoms. Although these patients are severely ataxic as well, they do not experience vertigo but rather an inability to stabilize their gaze while their head is moving (known as oscillopsia) that is very distressing. While a acute loss of one or both vestibular inputs results in a range of disabilities, patients with congenital or early-acquired BVL do not experience similar symptoms. Vestibular input plays such a crucial role in our sense of position in space and is so intimately linked with incoming tactile, proprioceptive, and visual information that the effects of its absence reach far beyond imbalance (Angelaki & Cullen,

2008). BVL has been shown to be associated with problems in spatial orientation (Hufner et al., 2007; P. F. Smith & Zheng, 2013), attention (Andersson, Hagman, Talianzadeh, Svedberg, & Larsen, 2003; Yardley et al., 2002) and even cognitive dysfunction including memory loss (P. F. Smith, Darlington, & Zheng, 2010), reading difficulties (Braswell & Rine, 2006), and poor school performance (Franco & Panhoca, 2008). In the congenital setting, infants with BVL can have delay of both gross and fine motor development (Kaga, 1999; Kaga, Shinjo, Jin, & Takegoshi, 2008). Although the onset of walking can be delayed by up to two years, children with BVL do eventually achieve their major motor milestones (Kaga, 1999; S. R. Wiener- Vacher, Obeid, & Abou-Elew, 2012). In typically developing children, the vestibular system is functional at birth but vestibular input plays a less prominent role relative to vision until age 6-7 years at which point adult type integration is established (O'Reilly, Mortlet, & Cushing, 2013). It is possible that this reliance on vision persists in children with BVL as a potential compensatory strategy. Importantly, deafness can also induce visually based compensatory strategies as evidenced by enhanced visual and tactile performance scores which are likely underpinned by cortical reorganization (Bavelier et al., 2001; Bavelier, Dye, & Hauser, 2006; Finney, Clementz, Hickok, & Dobkins, 2003; Lomber, Meredith, & Kral, 2011). Children who are deaf show increased cortical processing devoted to peripheral vision, which is of particular importance in balance (Finney, Clementz, Hickok, & Dobkins, 2003; Hatzitaki, Zisi, Kollias, & Kioumourtzoglou, 2002; Parasnis & Samar, 1985). It is possible that the increased reliance on vision in children with BVL and congenital deafness may also rely on this cross modal reorganization.

While hearing has not traditionally been considered in the triad of sensory input to balance, emerging evidence suggests that sound can affect postural control and the perception of self- motion. Sound carries important spatial information about objects outside of our visual field and humans are able to localize sound emitting objects with surprising accuracy within auditory space. Tanaka et al. demonstrated an increase in postural sway when participants were subjected to laterally moving auditory stimulus when eyes were closed (T. Tanaka, Kojima, Takeda, Ino, & Ifukube, 2001). These findings indicate that humans may also orient their posture in relation to sound in certain circumstance. The visual and auditory systems are intimately linked and sound may also serve to enhance our perception of visual movement. The addition of sound has been able to enhance illusory self-motion known as vection experienced when optic flow is induced in

the absence of actual physical movement (Riecke, Väljamäe, & Schulte-Pelkum, 2009). Auditory input appears to increase the salience of the visual input to enhance the illusion (Riecke, Väljamäe, & Schulte-Pelkum, 2009). Vection has also been shown to occur in the presence of moving auditory stimulus alone in about 25-60% of people although this is generally weaker than vision alone (Riecke, Väljamäe, & Schulte-Pelkum, 2009; Väljamäe, 2009). These findings highlight the importance of sound in our sensory construct of the world, but at the same time, indicate that it plays a less important role in the presence of more powerful environmental cues such as vision. Interestingly, blind individuals have been shown to perceive auditory motion more accurately than their sighted peers (Lewald, 2013). While this was true for moving sounds, they were only slightly better at the localization of stationary sound emitting objects. This difference may be the result of blind individuals using active head and body movements to create self-induced auditory flow out of surrounding sound sources. In this way they are able to couple the auditory flow with efference-copy, proprioceptive and vestibular information to create a more accurately calibrated version of their sound environment. Coupling of auditory and vestibulomotor systems likely occurs in sighted individuals as well but on a less significant scale. The central nervous system appears to be able to deftly switch between sensory systems in a context specific manner, ignoring a conflict sense or relying more heavily on functional senses when one is missing altogether. Such up-weighting of non-vestibular inputs is likely to occur when vestibular information is deprived. We hypothesize that given the important spatial information available through binaural hearing; sound input may of benefit to balance in such instances. Unfortunately, in children vestibular loss is most commonly associated with cochlear dysfunction and therefore the impact of hearing on balance has gone largely under studied in the pediatric population.

Children who are deaf are now able to access sound through CIs. The CI is an auditory prosthesis, which is made up of an array of electrodes, which is surgically placed into the cochlea and delivers electrical pulses to stimulate the auditory nerve. Each electrode is assigned a range of acoustic frequencies in such a way as to mimic the normal arrangement of frequencies in the cochlea. It is known that reestablishment of auditory input stimulates areas of the brain dedicated to the auditory system. With ongoing CI use, development occurs along the previously deprived auditory pathways from the auditory nerve and brainstem to thalamocortical areas (K. A. Gordon et al., 2011). Gordon et al., has demonstrated evidence for maturation of the rostral auditory

brainstem and cortex with implant use (K. A. Gordon et al., 2011). Children with bilateral implantation achieve a number of benefits associated with binaural hearing such as improved speech perception, hearing in noise and sound localization (Chadha, Papsin, Jiwani, & Gordon, 2011; J. D. Ramsden et al., 2012; Salloum et al., 2010; Steffens et al., 2008; R. J. M. van Hoesel & Tyler, 2003). As a result, children with bilateral CI and BVL present a unique opportunity to study the impact of sound on balance.

1.3 Research Objectives

The following work is driven by three main objectives. First, understanding if the BOT-2 is able to detect subtle changes in balance by comparing it to objective measurements of head, trunk, and centre of pressure will help physicians clinically by providing a more accurate understanding of the balance deficits represented by a given BOT-2 score. Therefore, our first objective is to determine if the BOT-2 correlates with objective, quantifiable measures of balance such as posturography using force plates and measurements of angular deviations of the head and trunk and to determine if these methods can be used to accurately differentiate between two groups of children with known vestibular function and dysfunction. We hypothesize that 1) as balance abilities demonstrated by BOT-2 scores decrease, angular deviations of the body segments and posturographic measures will increase and 2) these measures will show significant differences between our two groups while attempting to balance during the static tasks of the BOT-2.

Second, in the absence of vestibular input humans must use other senses to determine their position in space. Children with BVL appear particularly adept at doing this considering their ability to participate in many childhood activities. Vision appears to be a likely candidate given its already important role in balance. As such, our second objective will be to examine the role of vision in balance in children with BVL. The availability of visual information while balancing appears to improve performance of static balance tasks in simple visual scenarios like a clinical environment. We also wish to determine the extent to which more complex visual environments, as experienced in the real world, impact the benefit of the additional visual input to balance control. In this study, we will investigate the roll of a dynamic visual environment where objects in the environment move around the participants, as they would experience when standing at a street corner. We hypothesize that 1) deviations from neutral standing position of the head and

trunk, posturographic measures and time to fall will increase in the absence of vision (eyes closed) compared to in the presence of vision (eyes open) particularly in children with BVL compared to their typically developing peers and 2) that these measures will be greater when children balance in moving visual environments. This information can then inform therapy as it will allow more thorough counseling for patients and families about potentially dangerous situations.

Third, children with BVL who have bilateral CI have access to binaural sound cues, which could provide important spatial information and may be useful in postural control. We aim to 1) determine if sound input through CI can improve balance and 2) determine if the presence of directional sound cues (street sounds that are congruent with the street scene) impact balance differently than non-directional sound cues (white noise). We hypothesize that balance will be better when implants are on and that children will use binaural sound cues either through normal hearing or bilateral CI to improve their balance in the congruent sound environment.

By answering these questions we will have further defined balance deficits in children who have both auditory and vestibular dysfunction and will have identified their ability to compensate for these serious sensory deficits using additional spatial cues through restoration of auditory input. Moreover, if auditory input can be used to help patients navigate through their environments, this will provide clinicians with an additional tool to improve the lives of patients with bilateral hearing loss and vestibular impairment.

The following discussion will outline the anatomy and physiology necessary for understanding how the vestibular end-organs, housed deep within the temporal bone, inform the central nervous system of where we are and how we are moving in space.

1.4 Anatomy and Physiology of the Peripheral Vestibular System

The vestibular system informs our central nervous system of our position in space by sensing angular (e.g. during turning) and linear (e.g. ascending within an elevator) accelerations of our head. These two types of acceleration are sensed by two groups of fluid filled sensory organs housed within the bony labyrinth: the semicircular canals (SCC) and the otoconial organs. The three paired SCCs lie at orthogonal angles and detect angular accelerations around the yaw,

pitch, and roll axes. Angular head movements induce flow of the fluid, called endolymph, within the canal that is sensed by sensory epithelium of the organ. The sensory unit of the SCC is situated within ampulated end of the canal called the cristae ampularis. Each canal is maximally sensitive to motion in the plane of that canal and works as a functional pair with the contralateral canal oriented in a parallel plane (Figure 1.1). Motion occurring in the plane of the two paired canals is excitatory to one canal but inhibitory to its contralateral partner (e.g. turning the head to the left stimulates the left horizontal SCC, but inhibits the right horizontal SCC). This paired input is then integrated by the brainstem to determine the direction of movement and control balance. There are two otoconial organs, the utricle and the saccule. Although the otoconia share a common embryological origin with the SCC they are anatomically different. They are irregularly shaped ovoid structures that sit within the vestibule at right angles to one another. The utricle sits mainly in the horizontal plane (senses front-back movement and left-right movement) and the saccule sits in the vertical plane (senses up-down movement).

Figure 1.1. The semicircular canals work in functional pairs (demonstrated by the red and blue dashed lines). The posterior semicircular canal on the left corresponds to the superior semicircular canal on the right (red dashed lines).

The sensory epithelium of the vestibular system sits within the cristae of the SCC and the maculae of the otoconia. Hair cells within the cristae ampularis have their stereocilia, a specialized form of microvilli, located on the hair cell. One of these stereocilia is enlarged to form a kinocilium, embedded in the cupula. The cupula is a gelatinous mass that forms a fluid tight barrier within the ampulla of the SCC. Anchored firmly to the roof and lateral walls, movements of endolymph within the membranous labyrinth cause the cupula to bend and flex similar to a sail catching wind. These deformations cause sheer stresses that are detected by stereocilia. At rest when the head is kept still, hair cells emit a basal rate of neurotransmitter release. When movement of the head induces deflection of the hair cells towards the kinocilium the release of neurotransmitter from the hair cell is increased and increases the firing rate of the downstream vestibular neurons while movement away decreases the rate of firing as a result of a reduction in the release of neurotransmitter (Figure 1.2).

Within the utricle and saccule, the hair cells reside upon the macula. The cilia of these hair cells extend upward and are embedded within a gelatinous membrane that is analogous to the cupula of the SCC. However, it is distinct from the cupula in that is not attached to the surrounding walls of the vestibule and can therefore move freely within its corresponding plane. Located centrally within the membrane is the striola that provide an orientation point for the vestibular organs by dividing each membrane into two halves, where hair cells on each side have opposing orientations (e.g. to sense forwards and backwards, up and down).

The basal portion of the SCCs and the otoconial hair cells synapse with nerve fibers that make up the primary vestibular nerve. The primary vestibular nerve is a bipolar neuron with its cell body situated within the Scarpa’s ganglion. As mentioned, vestibular afferent neurons are continuously active even at rest, which permits striking sensitivity for signaling motion accelerations as the head translates and rotates in space. The vestibular nerve fibers are divided into two parts: the superior and inferior vestibular nerves based on the portion of the end organ that they innervate. The superior vestibular nerve (SVN) carries information arising from the cristae of the superior SCC, the horizontal SCC, the macula of the utricle and a portion the macula of the saccule. The inferior vestibular nerve (IVN) carries information from the posterior

Figure 1.2. The vestibulo-ocular reflex pathway. A head turn to the left (thick blue arrow) stimulates the left horizontal semicircular canal and simultaneously inhibits the right horizontal semicircular canal. The red line demonstrates the excitatory pathway that is initiated by stimulation of the canal to induce contraction of the ipsilateral medial rectus (MR) and the contralateral lateral rectus (LR) muscles to turn the eyes in the opposite direction of head movement and maintain stable gaze. The blue dashed lines depict the inhibition that occurs to allow for the “push-pull” relationship of the correlating muscles. At the bottom of the figure, the basal firing rate of the afferent neurons can be seen when the head is in a neutral position. When the head is turned to the left, the firing rate on the left increases and decreases on the right.

SCC as well as the remaining portion of the macula of the saccule. The SVN and the IVN join the cochlear nerve to form the 8th cranial nerve and terminate at the vestibular nucleus found within the floor of the 4th ventricle. The vestibular nucleus has four parts: the inferior, superior, medial and lateral (also known as Deiters’ nucleus), which helps determine what will be done with the head position information. Some fibers bypass the vestibular nucleus to directly inform the cerebellum of our body position. The vestibular system is the only system to send projections directly to the cerebellum without synapsing first. Projections that do synapse within the vestibular nucleus are relayed to multiple sites throughout the spinal cord, brainstem and brain.

Our positional relationship with the external environment, informed in part by the vestibular system, is critical not only as a frame of reference for mediating intersensory disputes but also as a means to maintain gaze, upright posture and to carry out crucial autonomic functions. For example, nerve fibers originating in the vestibular nucleus spread through the brainstem to interact with the solitary, vagal and parabrachial nuclei. In this way, the vestibular system can inform the autonomic system, ensuring accurate modifications are made to our heart rate and blood pressure to meet our ever changing position in space (Shortt & Ray, 1997; K. Tanaka, Abe, Awazu, & Morita, 2009). In the following sections, we will review the reflex pathways informed by the vestibular system in order to maintain stable gaze and posture.

1.4.1 Vestibular Reflex Pathways

The vestibular system provides inputs for three reflexes pathways that are important for maintaining stable vision and posture in relation to our movement and environment. These are known as the vestibulo-ocular reflex, the vestibulospinal reflex, and the vestibulocollic reflex.

The vestibulo-ocular reflex

Objects of visual interest must be kept on the fovea of the retina where visual acuity is highest. To look at an object of interest that comes to our attention, a rapid movement of the eye is generated by the central nervous system known as a saccade to bring the object of interest onto the fovea. As our head moves in space, the projected image of that object changes on the retina unless compensatory movements of the eye are made. Slow movements including vestibulo- ocular reflex (VOR), smooth pursuit, and optokinetic nystagmus keep the target on the fovea.

The VOR uses vestibular information to control eye movement in a three-neuron arc (Figure 1.2). Information regarding head movement (e.g. rotating the head to the left) is sensed by the vestibular organs and travels to the vestibular nucleus. Here, second order neurons ascend by the medial longitudinal fasciculus to the extraoccular motor nuclei that will generate an equal but opposite rotation (e.g. rotation to the right) of the eyes. In order to achieve conjugate movements of the eyes, differential impulses must be sent to variably contract and relax the extra-ocular muscles of each eye in a complementary, coordinated manner often commonly referred to as a “push-pull” pattern (Figure 1.2). The VOR can be observed clinically by performing a head thrust test and observing the eyes of a patient attempting to maintain their gaze on a fixed target or by caloric stimulation of the horizontal SCC. The reflexive slow component of the VOR that is generated by the vestibular system is present at birth, although time constants are approximately half of normal adult values in the first week of life, reaching adult speeds by two months of age (Weissman, DiScenna, & Leigh, 1989). The centrally mediated fast component (saccade) is variably present and inaccurate, likely due to immaturity of the visual pathways at birth and continues to develop until about two years of age (Ornitz, Kaplan, & Westlake, 1985).

The vestibulospinal and vestibulocollic reflexes

The CNS is constantly evaluating incoming information regarding body orientation and gravity to make appropriate postural adjustments. This information is combined with tactile and proprioceptive information and is used to inform axial musculature of head position in space to stabilize the body and maintain postural control. This is achieved by descending secondary neurons from the vestibular nucleus that project to the spinal cord. These second order vestibular neurons also receive modifying input from the cerebellum and cerebral cortex prior to descending through the spinal cord.

There are two functionally distinct descending projections for balance and coordinating head and eye movements: the lateral and medial vestibulospinal tracts. The lateral vestibulospinal tract arises from the lateral vestibular nucleus and descends ipsilaterally but innervates bilateral anterior horn cells to generate and modify deep tendon reflexes of the so-called anti-gravity musculature of the neck, back, hips and legs. This pathway is known as the vestibulospinal reflex (VSR). Similar to how the VOR works to contract and relax the paired ocular muscles to achieve

appropriate compensatory eye movements, the VSR creates similar push-pull arrangement of agonists and antagonists across the neural axis, which is crucial for generating the compensatory movements needed for balance and upright stance. Unlike the VOR, the VSR takes longer to develop with observable differences between children and adults until about 14–15 years of age (Rine, 2007). Linear, “up-down” translations commonly experienced during walking where the head is jarred by the impact of heel strikes are detected by the saccule. This input is transmitted along the inferior vestibular nerve to the vestibular nucleus. The medial vestibulospinal tract originates in the medial vestibular nucleus and descends bilaterally in the spinal cord but only to the neck and upper thoracic spinal cord. Through this vestibulocollic reflex (VCR) the vestibular organs may stimulate patterned contractions of the neck musculature to reduce involuntary oscillations of the head during running and walking to create a stable platform and further stabilize vision. This pathway can be observed directly in the clinic or laboratory setting using vestibular-evoked myogenic potentials. Here, sound inputs are used to stimulate the saccule that sends an inhibitory signal to the sternocleidomastoid muscles and the brief inhibition of motor unit discharge can be detected with surface electrodes.

Cortical and cerebellar projections of the vestibular nucleus

Secondary fibers originating from the superior, medial, and inferior vestibular nuclei ascend bilaterally to the ventral posterior nucleus of the thalamus. Unlike other sensory system, there is not a single cortical area where vestibular information converges and as such there is no identifiable “vestibular cortex”. Rather there is an extensive network of vestibular inputs that project to numerous regions of the brain, underlining the far-reaching effects and importance of vestibular input. From the thalamus, some tertiary neurons continue to ascend to three important sites of vestibular processing within the parietal lobe and insular cortex that form an interconnected network that integrates vestibular information with joint proprioception as well as orientation and perception (J. H. Martin, 2012). The retroinsular cortex and posterior parietal lobe play roles in conscious awareness of our body’s orientation and movement as well as the orientation of the world around us (Brandt & Dieterich, 1999; Deutschländer et al., 2002; J. H. Martin, 2012). The third main site, area 3a of the primary somatic sensory cortex, which is thought to participate in combining head position information with proprioceptive afferents from the neck musculature (Odkvist, Schwarz, Fredrickson, & Hassler, 1974; Sugiuchi, Izawa, Ebata,

& Shinoda, 2005). Many of these sites have descending projections to the vestibular nuclei to further modify information that will be transmitted down the medial and lateral vestibulospinal tracts for postural control.

The cerebellum is also a crucial component of the balance system that helps integrate head- referenced vestibular information with information from the outside world. The flocculonodular lobe of the cerebellum receives information both directly from the primary vestibular afferents and indirectly via secondary vestibular neurons in the vestibular nuclei (Voogd, Gerrits, & Ruigrok, 1996). Purkinje neurons of the flocculonodular lobe send axons to the medial, inferior and superior nuclei to help control head and eye movement via the medial vestibulospinal tract (Wylie, De Zeeuw, DiGiorgi, & Simpson, 1994). The fastigial nucleus of the cerebellar vermis selectively computes information regarding translation rather than acceleration and together with the vestibular nucleus provides critical information regarding how the head moves in space. The cerebellum is also known to be involved in compensation of vestibular loss related to the VOR and motor learning (O'Reilly, Mortlet, & Cushing, 2013)(Cushing book). Adaptive changes in the vestibulocerebellum and vestibular nucleus have been demonstrated in animal experiments (Johnston, Seckl, & Dutia, 2002). The error message that are used by the cerebellum to adjusted occulomotor responses during compensation arrive via mossy fibres arising in the inferior olives of the brainstem that receive inputs from the visual system. The cerebellum then compares visual inputs to incoming vestibular inputs regarding head position resulting in long lasting adaptive changes that appear to be sustained over long periods of time (Lisberger, 1998).

From the diverse anatomic sites that receive vestibular input it is clear that the vestibular system plays an important role in shaping our sensory percept of the world. It does not do this on its own and requires extensive integration with other sensory inputs through the CNS.

1.5 Integration of Vestibular Information

Signals from muscles, joints, skin, eyes and the auditory system are continuously integrated with vestibular inflow to provide up-to-date information about where we are in space. Central vestibular processing is highly conservative and strongly multimodal. Vestibular information does not give rise to a distinct conscious sensation, in part, due to the extensive and early multimodal convergence of the different inputs. While responsible for separate kinds of

movement, the SCCs and otoconia are complementary and their combined activation is necessary to comprehend the range of motion experienced in everyday life. Integration of vestibular information occurs almost immediately with canal/ otoconial information being combined and processed at the first synaptic junction within the vestibular nucleus and the cerebellum. This allows us to resolve ambiguities in linear movements and accelerations of the head almost immediately.

More complex, visual-vestibular and proprioceptive-vestibular interactions occur through the central vestibular pathways and are vital for gaze and postural control reflexes as alluded to above. While the neural basis of cue integration is still not well understood, areas of multimodal neurons are being identified. For example, a population of multimodal neurons in the dorsal medial superior temporal area located in the extrastriate visual cortex and the ventral intraparietal cortex that may be a potential candidate neuronal substrate for this integration (Gu, DeAngelis, & Angelaki, 2007; Takahashi et al., 2007). Neurons within this area appear to be selective for heading based on optic flow and vestibular cues. As mentioned, proprioceptive and vestibular information is also intimately linked and are integrated at multiple levels. Animal models have suggested that proprioceptive and somatosensory information interact with the vestibular nucleus directly through dorsal column projections (Anastasopoulos & Mergner, 1982; Boyle & Pompeiano, 1980). At the cortical level, area 3a of the primary somatic sensory cortex may be important for relating head position information with proprioceptive afferents from the neck musculature (M. Gabriel, Frippiat, Frey, & Horn, 2012). Finally, the cerebellum appears to be an important area for proprioceptive-vestibular integration. Proprioceptive inputs interact with vestibular inputs within the rostral fastigial nucleus of the cerebellum, which is vital for accurate control of posture and balance (Furuya, Kawano, & Shimazu, 1975; Shimazu & Smith, 1971).

These interactions contribute to a surprising range of functions beyond staying upright, impacting the highest levels of perception and consciousness. Vestibular information provided in the ascending pathways to the limbic system and neocortex is required for an accurate internal representation of the relationship between the self and the spatial environment (Angelaki & Cullen, 2008). In the absence of this information, this internal representation can become inaccurate or ambiguous, and cognitive performance is affected (Angelaki, Klier, & Snyder, 2009; P. F. Smith & Zheng, 2013). Spatial memory mediated by the hippocampus appears to also

require vestibular input (Peruch et al., 1999; Zheng, Darlington, & Smith, 2006; Zheng, Goddard, Darlington, & Smith, 2009). Although it is not clear how vestibular input arrives in the hippocampus, research suggests that vestibular information must be transmitted to the hippocampus in order to be integrated with other sensory information relevant to spatial memory (P. F. Smith & Zheng, 2013). Here the vestibular system modulates place cells that respond to specific places in the environment (Gavrilov, Wiener, & Berthoz, 1996; Wiener, Korshunov, Garcia, & Berthoz, 1995). Both human and animal studies have demonstrated that disruption of the normal vestibular function can result in spatial memory deficits (H. S. Cohen, 2000; Peruch et al., 1999; Zheng, Goddard, Darlington, & Smith, 2009). Non-spatial information associated with place is also integrated here. Interestingly, auditory stimulation including noise trauma has been reported to affect place cell function within the hippocampus suggesting that auditory input also contributes to spatial memory within the hippocampus (Goble, Møller, & Thompson, 2009).

Achieving this level of coordination and integration does not come easily to humans. Watching a child learn to stand and walk demonstrates that point easily enough. As we will discuss in the following section, development of postural control and the ability to appropriately interact with our environment takes years of work as sensory and effector systems come together.

1.6 Development of Postural Control

Balance control is required in both posture and locomotion. In order to achieve balance, one must develop the ability to control the centre of mass (COM) in relationship of the base of support (BOS). The COM is generally defined as a point that is at the centre of the total body mass where the weighted relative position of the distributed mass sums to zero. In a complicated form such as the human body, the COM is calculated from the weighted average of the COM of each body segment (Shumway-Cook & Woollacott, 2007). The vertical projection of the COM onto the support surface is the centre of gravity, but the two terms are commonly used interchangeably. The BOS is the area of the body that is in contact with the support surface. Balance means keeping the COM within the confines of the BOS. It is felt that the COM is the key variable controlled by the postural control system (J. Scholz et al., 2007). In quiet stance, small amounts of sway can be observed as we test the limits of our BOS. A fall results when the

COM exceeds the borders of the BOS. The central nervous system applies small amounts of the force to the ground through contractions of the hip and leg musculature in order to nudge the COM back into a safe position. The distribution of the total force applied to the support surface is called the centre of pressure (COP), and it continuously moves around the COM to keep it within the BOS (Benda, Riley, & Krebs, 1994). The COP can be measured in the laboratory by having study participants stand on force platforms. Force platforms are a form a kinetic analysis that measure ground reaction forces beneath the feet that are proportional to the COP (Winter, Patla, & Frank, 1990). Since the COM is central to this process and itself made up of the average of multiple body parts, this means that postural control is a careful balancing act that requires consideration of each body segment in relation to gravity and our environment. In many species, upright posture is present at birth but in humans it is learned over time as we acquire and mature our sensory and motor systems (Garwicz, Christensson, & Psouni, 2009). We will consider this process briefly in the following section.

Development of postural control in children is a fascinating and dynamic process. In typically developing children, the acquisition of postural stability occurs in a cephalocaudal fashion, where infants first achieve control of the head followed by the trunk and eventually upright stance (Gesell, 1946; Shumway-Cook & Woollacott, 2007). One of the first indications of postural control can be observed in newborn infants orienting their head slowly towards an auditory source (Muir & Field, 1979; Savelsbergh, Netelenbos, & Whiting, 1991). Coupling of vision, head orientation and hearing is important, as sound will remain an important method of directing attention for the remainder of the infant’s life. The dynamic systems model of motor development has been proposed to explain how children acquire new motor skills. In infants, new behaviors and skills emerge from the interaction of the child (and the maturing nervous and musculoskeletal systems) with the environment (Shumway-Cook & Woollacott, 2007; Thelen, 1989). The emergence of postural control requires development and coordination of sensory and motor systems in relation to environmental conditions. Increased muscle strength is required to achieve increasingly demanding motor milestones but the increase in complexity of those milestones also demands increasing coordination of neuromuscular response synergies and the development of internal representations to map motor action (Shumway-Cook & Woollacott, 2007). Sensory systems must develop to inform these systems and allow coordination of actions. Whereas in adults the sensory systems function in an organized and context specific manner

where inputs are weighted based on the conditional requirements, many of the sensory systems in children are not yet fully established (Shumway-Cook & Woollacott, 1985). Appropriate internal representations related to posture are required in order to organize sensory inputs and coordinate them with motor actions. For example, as a child begins to move through a gravitational environment, sensory and motor maps would develop that relate to incoming sensory inputs from the visual, somatosensory and vestibular systems. As mentioned earlier, the vestibular system is the first sensory system to develop in utero and is fully formed at the time of birth; however, it requires approximately two months before reaching adult type latencies and full functionality and integration with other sensory systems can take years (Weissman, DiScenna, & Leigh, 1989). Children often opt to use vision for balance, particularly when a newly acquired skill is emerging. Butterworth & Hicks exposed infants at different stages of development to a moving-room paradigm (Butterworth & Hicks, 1977). Infants who had recently learned to sit, showed complete loss of balance in response to this visual stimulation. However, with increasing experience the response amplitude significantly declined and children were able to remain upright. These results suggest that while children appear to rely almost exclusively on vision during developmental transitions, increasing experience allows use of somatosensory and vestibular inputs. More difficult static balance strategies, such as standing on one foot, require feedback mechanisms that involve vision, in particular peripheral vision, to stabilize (Hatzitaki, Zisi, Kollias, & Kioumourtzoglou, 2002). The ability of the central nervous system to interpret and use peripheral visual cues is associated with increased accuracy and consistency of eye movements. It is possible that the acquisition of head stabilization strategies that occurs around 7 years of age is essential for this and may reflect maturation of the vestibular system that provides information about head position relative to the supporting surface. Eventually in adulthood, a head-stabilization in space strategy is adopted most of the time (Amblard, Assaiante, Fabre, Mouchnino, & Massion, 1997; Assaiante, 1998; A. M. Bronstein, 1988). Children begin to use somatosensory inputs around 3-6 years of age, but full use may take as long as 9-11 years (Foudriat, Di Fabio, & Anderson, 1993). With time, this will become the preferred input for static balance and the vestibular system will be relied on more when there is intersensory conflict to suppress misleading information.

The onset of walking is often delayed in children with BVL. While the focus of the present work will be on static balance, development of locomotion relies on many of the same senses and will

be discussed here in brief. Assaiante et al. have proposed that locomotor function progresses in a stepwise fashion over four successive periods (Assaiante, 1998; Assaiante, Mallau, Viel, Jover, & Schmitz, 2005). The first stage occurs from birth to the acquisition of upright stance. Here, the development of postural responses occurs along a cephalocaudal gradient. Adequate control first occurs in the muscles of the neck, followed by the trunk and finally the legs. When making forward movement infants and young children in this stage appear to prefer activating neck musculature prior to trunk muscles. Movement between the head and body segments appear to occur in an articulated fashion. Next, the second period takes place from the acquisition of upright stance to about 6 years of age. This period is characterized by mastery of the effectors and development of coordination between the lower and upper body parts necessary for walking. This is likely delayed, as it requires maturation of the postural control system involving the cerebellum and vestibular structures. During this stage children prefer to use “en-bloc” strategies to limit movements at joints between body segments to reduce the complexity of locomotor balance strategies as the postural control systems develop. The third period takes place from approximately seven years to adolescence. A return of an articulated mode of head-trunk operation, where head stabilization is necessary to serve as a reference frame to design motor organization plans during more complex locomotor tasks. Here, the head can be seen as fixed in place to create a stable-platform for the sensory systems of the head. This stability is achieved by creating counter rotations of the neck to compensate for posture stabilizing movement of the torso needed as the child begins to utilize more challenging motor skills during exploration and play (Nicholas, Doxey-Gasway, & Paloski, 1998). While articulation increases the complexity of segmental motor plans, it simplifies the sensory task of separating gravitational information from the otoconia and linear accelerations making exploration of new environments possible (Nicholas, Doxey-Gasway, & Paloski, 1998). Progression through the steps likely reflects the availability and importance of the various sensory inputs during ontogenesis as with stationary balance tasks. Vision plays an important role in children as they attempt to master new postural challenges such as sitting without support, independent upright stance and independent walking that likely persists until about age 6 years. A transient disappearance of the peripheral visual contribution to dynamic balance control takes place at around age 7, which corresponds precisely with the beginning of effective head stabilization while walking. This new ability is generally assumed to be mainly of vestibular origin that may transiently predominate as the main sensory

input for organizing balance strategies. The fourth period is not reached until adulthood when the three sensory inputs can be coordinated and recruited independently to improve equilibrium and an articulate head-trunk strategy can be used in all circumstances.

1.7 Methods of Assessment of Balance Function in Children

Given the evolving nature of balance and postural control, measuring motor skill development and balance in children is challenging. Gross motor assessment of infants, children, and adolescents vary, and must reflect the stage of development of the individual. Assessments must reflect stationary and walking balance and must consider factors such as strength, range of motion and coordination. Clearly, comparison of different ages is a challenge given the significant functional leaps that are made during a child’s motor development, but from the perspective of rehabilitative goals it is important as well. It would be unreasonable for a therapist to expect a child to hop on one foot if they have not yet mastered the one-legged stance. Early in life, evaluation of gross motor function in infants consists of review and assessment of gross motor milestones as we have previously reviewed. Additionally, noting the waxing and waning of so-called primitive reflexes allows early assessment of the coordination and integration of sensory input and motor outputs. Here we will briefly review a selection of commonly used balance assessments in children.

The Rhomberg test was one of the first clinical maneuvers developed to assess static balance. In this test, patients are simply asked to stand still with feet parallel and arms outstretched with eyes open then and closed. Classically, significant increases in posterior and lateral sway following closing of the eyes were felt to be pathognomonic for tabes dorsalis, also known as syphilitic myelopathy. In fact, it was so strongly associated with the disease that it had made its way into popular culture and an accurate description of the Rhomberg in such a patient can be found in Rudyard Kipling’s popular short-story “Love-o’-Women” (Vora & Lyons, 2004). Now it is known that a positive Rhomberg is indicative of any impairment of proprioceptive information coming through the dorsal columns. Multiple quantitative and qualitative methods now exist for assessing balance and postural control and some of the more common methods will be discussed in the following sections. Since postural control and motor development are linked in the pediatric population, methods of assessing motor control will also be included in this discussion.

1.7.1 Posturography

Posturography is the quantitative extension of the Rhomberg test. It uses force platforms to record the trajectory of the COP, which is proportional to the ground-reaction torque. The COP is usually expressed as displacement, variability or velocity. Posturography can be done statically on a horizontal, unperturbed surface or dynamically where perturbations are induced. Computerized Dynamic Posturography (CDP) offers a quantifiable method of measuring static balance that also assesses the impact of the three cardinal senses of postural control: visual, vestibular and proprioceptive (and somatosensory) input. The sensory organization test (SOT) is the most commonly employed method of assessing the relative contributions of those senses. This test selectively removes vision by closing the eyes, moving a visual screen while the eyes are open, or moves a platform on which the patient is standing. Various commercial systems are available that can calculate a patient’s score that can be compared with normative data for either children or adults (Ferber-Viart, Ionescu, Morlet, Froehlich, & Dubreuil, 2007). The modified Clinical Test of Sensory Interaction on Balance (mCTSIB) is a simplified derivative of the SOT (H. Cohen, Blatchly, & Gombash, 1993; Shumway-Cook & Horak, 1986). Here, COP is measured by force platforms as the patient stands with feet parallel either on a flat surface or unstable, foam surface repeating each task with eyes open and closed. While these tests can provide valuable, quantifiable insights into the interaction of sensory systems in balance, their clinical utility is limited by the cost, time required for testing, and space requirements of CDP (M. K. Park et al., 2013). Moreover, to accurately reflect the evolving acquisition of skills that involve balancing while both standing still and walking, balance assessments must incorporate both of these conditions.

1.7.2 Imaging Measurement Techniques

Posturography using force platforms assumes a single mass, inverted pendulum model, where the subject is assumed to be in a sentry-like position (Figure 1.3a&b) (Johansson, Magnusson, & Akesson, 1988; E. Park, Schöner, & Scholz, 2012). This is may be appropriate for simple stances where participants are looking directly ahead. In this stance, the fixed point of the pendulum is the ankle joints, which are primarily in control of quiet standing posture (Winter, Patla, Prince, Ishac, & Gielo-Perczak, 1998). However, as task and/or environmental constraints increase the

difficulty of postural control, the hips become involved, creating a break in the pendulum (Kuo, Speers, Peterka, & Horak, 1998; Nashner, 1985). Even in quiet stance, humans are usually scanning the environment, which requires articulation at the cervical joint (E. Park, Schöner, & Scholz, 2012). Although this does not appear to affect the COM appreciably, control of the cervical joint is critical for maintaining vision and correct interpretation of vestibular inputs and should also be considered in the evaluation of postural control (Barin, 1989; Nicholas, Doxey- Gasway, & Paloski, 1998; E. Park, Schöner, & Scholz, 2012). As such, it would seem that a single, inverted pendulum model inadequately describes human movement, even at rest. Imaging measurement techniques use video imaging or optoelectronic techniques such as motion capture to quantify how the body moves Figure 1.3. Segmental analysis of the human body. Conventional posturography assumes (Winter, Patla, & Frank, 1990). The use of that the human body behaves as an inverted motion capture allows evaluation of multi- pendulum (A), with a single fixed point about which the pendulum swings (B). segment postural control (Figure 1.3c) Analysis using motion capture takes into (Nicholas, Doxey-Gasway, & Paloski, 1998). consideration the multiple, highly mobile joints of the human body (C). Here, light emitting or reflective markers are placed at joints or on predetermined locations on each body segment. One or more detectors are then used to follow these markers through space. Markers can be placed over specific areas of interest such as the head and trunk and lines can be drawn between markers to measure angular deviations of those segments. Using motion capture allows evaluation of the relative contributions of each body segment to gain better understand the physiology of postural control. Alternatively, it may also provide insights into how these segments are related in pathological states and may yield targets for rehabilitation.

1.7.3 Assessment of Balance and Motor Control in Children

The Movement Assessment Battery for Children

One commonly employed test is the Movement Assessment Battery for Children (M-ABC) from 4-12 years old (Henderson & Sugden, 1992). This test evaluates eight tasks grouped by manual dexterity, ball skills, and dynamic balance. The test has been shown to have adequate reliability and validity for assessment of mild to moderate motor impairments and as a measurement of motor ability in children it does not have the ability to be converted to a standardized score (Croce, Horvat, & McCarthy, 2001).

The Köperkoordinationstest für Kinder (Body Coordination Test for Children)

The Köperkoordinationstest für Kinder (KTK) was developed by Kiphard and Schilling in 1974 (Schilling & Kiphard, 1974). It is comprised of a standardized normative instrument that measures gross motor coordination for children ages 5-14 years. The KTK uses four dynamic balance tasks including: 1) walking backwards on balance beams of diminishing width, 2) hopping on one leg over an increasing number of foam floor plates, 3) jumping laterally, side-to- side with legs together, 4) moving across a floor by stepping from one foam plate to another. While the KTK is considered to be a reliable test for measuring gross motor coordination in children, it involves multiple pieces of equipment and requires a significant amount of space, reducing its usefulness as an assessment tool in a busy Otolaryngology – head and surgery clinic.

The Bruininks-Oseretsky Test of Motor Proficiency

The Bruininks-Oseretsky Test of Motor Proficiency (BOT-MP) assesses a wide range of motor skills including: fine motor skills, strength and agility, body coordination static and dynamic balance in children age 4 to 21 years of age (R. Bruininks & Bruininks, 2005). It is one of the most widely used balance tests in children and is often used as the control for validation studies of other motor tests. It requires little space and equipment and can be done in less than 10 minutes. The balance subtest (referred to hereafter as the BOT-2) will be described in detail in the methods section but in brief, consists of nine skills incorporating standing and walking tasks performed with eyes open and closed. The BOT-MP has been used to study motor function in

children with horizontal canal dysfunction and hearing loss (F. B. Horak, Shumway-Cook, Crowe, & Black, 1988). They found that reduced or absent vestibular function in the children with hearing impairment did not affect the development of motor proficiency, but that balance skills were significantly reduced. This validation in our population of interest makes it particularly appropriate for use in an Otolaryngology-head and neck surgery clinic.

Posturography and clinical balance tests are both useful in the assessment of postural control and balance. Assessments of posturography such as the mCTSIB or SOT can be considered process- oriented assessment tools for evaluating the strategies used to control balance (De Kegel et al., 2010), whereas clinical balance tools are product-oriented, that is, they evaluate the functional results of central nervous system strategies for postural control (De Kegel et al., 2010). By allowing evaluation of multi-segment postural control, motion capture analysis may serve as a link between these two processes. As such, these measures provide different, but complementary information and assessment protocols should consider implementing aspects of all three.

1.8 Assessment of Balance in Real-World Environments

Whenever possible, experimental conditions must recreate the target environment as closely as possible. For children, the target environment ranges from noisy classrooms to chaotic schoolyards or even a busy street, none of which lend themselves easily to scientific study. Balance assessments could be performed in a playground; however, this is neither practical nor safe. Considerable effort over the last 50 years has gone into developing virtual environments in order to measure physiological phenomena in natural environments. A number of methods for assessment exist to do this and while an extensive review of these methods is beyond the scope of this work we will briefly touch on some of the more common methods before describing our particular set up.

Classic Desktop Systems

This type of set up has been in use for over 50 years and consists of a single user sitting in front of a computer or television screen. The user may navigate through an environment on the screen using a joystick or keypad (Figure 1.4a). The virtual environment may accurately represent a given environment and if the set up includes speakers a congruent sound environment can also

be established (Chance, Gaunet, Beall, & Loomis, 1998). The system is cost-effective and can be installed on most computers making it widely available (Waller & Hodgson, 2013). Motion can be simulated by inducing optic and auditory flow. However, users typically do not become fully immersed in the virtual environment and all internal representations of a participant’s position will accurately report that the person is sitting in front of a computer screen.

Figure 1.4: Methods of testing in virtual environments. A) Classic desktop system. Study participants sit in front of a computer screen and use a joystick or keyboard to move through the virtual world on the screen. B) Head mounted display. Study participants wear the head mounted display (inset, image from http://www.worldviz.com/products/head-mounted-displays) and are able to move freely through the environment. C) CAVE set-ups. Study participants are actually immersed within a room comprised of projection walls to create a virtual environment. The CEAL StreetLab shown above (taken from www.idapt.com) is unique in that a treadmill can be placed inside to allow navigational studies as well.

Head mounted displays

In head mounted displays, the virtual environment display is worn on the head of the study participant as they perform the study tasks (Figure 1.4b). This allows participants to move freely as they are not confined to the test space, which lends this set up well to locomotion studies. The head-mounted display allows better immersion in the virtual environment than the desktop display and since participants are able to walk and move through the task, internal representations are congruent with the activity. Scenes are projected on the displays set just in front of the users eyes. The field of view is dependent on the device but can range greatly.

Peripheral vision is often limited by the head display, which is an important consideration in balance studies where peripheral vision is important.

Cave Automatic Virtual Environment

A Cave Automatic Virtual Environment (CAVETM) consists of three or more large projection screens that make up the walls of a room (Waller & Hodgson, 2013). Occasionally the floor and ceiling also serve as projection screens (Figure 1.4c). Here, rather than viewing the virtual environment on a single screen or monitor, the participant can physically stand within the virtual environment. Depending on the number and placement of speakers, a 3D soundscape can be created as well. While immersed within such an environment, objects in the periphery can be seen in the participant’s peripheral vision. If an object in the periphery catches the participant’s attention and they wish to view it using more central vision, they can turn their head or body to see the object head on. As with head mounted displays this ensures that not only do vision and audition match the target environment, but internal cues of the participant are congruent as well. However, the size of the CAVE limits the amount of mobility and study of locomotion can be challenging. In this study we have used a virtual environment at the Challenging Environment Assessment Laboratory (CEAL) called Street Lab. The CEAL Street Lab is a modified version of a CAVE set up. The details of the Street Lab will be discussed below; however, in brief, Street Lab is large enough to perform the tasks of the BOT-2. Moreover, while navigation studies are often not possible in CAVE set ups, Street Lab can be set up with a treadmill. As participants walk along the treadmill, the virtual environment can be made to move past the participant creating the illusion of actual movement.

1.9 Cochlear Implantation and Vestibular Function

Surgical manipulation of the inner ear puts the vestibular apparatus at risk. Even non-destructive procedures involving the inner ear may impact vestibular function. Post-operative vertigo following stapedectomy has been reported at both early and late post-operative time points (Albera, Canale, Lacilla, Cavalot, & Ferrero, 2004; A. Ozmen et al., 2009; Parnes, Black, Wall, O'Leary, & Feltyberger, 1978). Transient vestibular dysfunction was found in up to 44% of these patients and impaired balance was demonstrated on both subjective and objective measures. Multiple intraoperative factors may contribute to these findings following otologic procedures

including: thermal injury from high speed drilling, serous labyrinthitis induced by opening of the membranous canal, entry of blood into the inner ear, or persistent leak of perilymphatic fluid (Albera, Canale, Lacilla, Cavalot, & Ferrero, 2004; Buchman, Joy, Hodges, Telischi, & Balkany, 2004). Specific to cochlear implant surgery injury has been reported relating to electrode insertion. Although pathological evidence is limited, Tien and Linthicum have reported fibrosis, hydrops with saccular membrane distortion, and reactive neuromas (Tien, 2002). It is not uncommon for patients to experience vertigo and imbalance following CI surgery, with reports ranging from 2-74% of patients (Enticott, Tari, Koh, Dowell, & O'Leary, 2006; Fina et al., 2003; Krause et al., 2009; Kubo, Yamamoto, Iwaki, Doi, & Tamura, 2001; Steenerson, Cronin, & Gary, 2001; Todt, Basta, & Ernst, 2008). In early reports, authors speculated that this might be due to electrical current spread from the implant device to the vestibular nerve (F. O. Black, Wall, O'Leary, Bilger, & Wolf, 1978; Ito, 1998). While current does appear to spread throughout outside the cochlea (Cushing, Papsin, & Gordon, 2006), multiple factors such as age, etiology of SNHL, surgical approach, method of assessment (questionnaires versus objective measurements of balance and end-organ function) may contribute (Bernard-Demanze et al., 2013; Kluenter, Lang-Roth, Beutner, Hüttenbrink, & Guntinas-Lichius, 2010; Micco & Richter, 2006; Todt, Basta, & Ernst, 2008). Transient vertigo following surgery is a common experience for post- operative patients and can often be the result of fluid imbalance or anesthetic breakdown products. However, vestibular end organ dysfunction has been demonstrated following CI surgery and may explain more persistent symptoms or imbalance. Impairment of saccular function measured by VEMP testing has been demonstrated in 30-92% of patients after CI surgery (Cushing, Gordon, Rutka, James, & Papsin, 2013; Jin, Nakamura, Shinjo, & Kaga, 2006; Licameli, Zhou, & Kenna, 2009). Licameli et al. found abnormal VOR gains in 60% of patients following CI insertion (Licameli, Zhou, & Kenna, 2009). Although only three patients tolerated bithermal caloric testing, all three had absent response ipsilateral to the implanted ear. Cushing et al. found absent saccular function in only 30% of unilaterally implanted patients (Cushing, Gordon, Rutka, James, & Papsin, 2013). Horizontal canal function was reduced in 50% of patients tested with caloric stimulation and 47% after rotational stimulation (Cushing, Gordon, Rutka, James, & Papsin, 2013). Interestingly, in their study, isolated unilateral vestibular losses were found to be distributed equally between the implanted and non-implanted side. While there are obvious risks to the labyrinth, the exact etiology of vestibular dysfunction

seen in CI users remains unclear given that many etiologies of SNHL also causes vestibular dysfunction as discussed above. Cushing et al found that the likelihood of vestibular end organ dysfunction was highly dependent on the etiology of SNHL. This would support the hypothesis that vestibular dysfunction predated the implantation surgery as a result of a common etiological origin. Buchman et al. reported abnormal caloric responses in 29% of “at risk” patients defined as those who had normal or reduced preoperative horizontal canal function (Buchman, Joy, Hodges, Telischi, & Balkany, 2004). They pointed out that given the low rate of “at risk” patients preoperatively, the risk of post-operative vestibular lesions resulting from cochlear implantation was quite low. They also noted that while some children did experience vestibular loss, they did not experience concurrent balance impairment when measured by CDP. While Licamelli et al. found somewhat higher rates of vestibular dysfunction in children, 61% still achieved normal sensory organization test scores on CDP (Licameli, Zhou, & Kenna, 2009). Suarez used force plates to assess balance in children with hearing loss and vestibular dysfunction (H. Suarez et al., 2007). They found that when visual and somatosensory information was available, a small group of children with vestibular dysfunction were able to achieve balance scores similar to those of typically developing children. Other groups have used the BOT-2 to assess balance in children who use CI and found significant impairment in static and dynamic balance in CI users compared to normal hearing controls (Cushing, Chia, James, Papsin, & Gordon, 2008; Cushing, Papsin, Rutka, James, & Gordon, 2008; Eustaquio, Berryhill, Wolfe, & Saunders, 2011). Although Suarez et al. did not see a difference based on etiology, Cushing et al. found that children with meningitis and vestibular dysfunction had an increased reliance on vision (Cushing et al., 2009). Children with vestibular loss who use CI may also use sound input to improve their balance. In Buchman’s study, CI users appeared to have improved CDP results after cochlear implantation. Moreover, Cushing et al. found that tests of static and dynamic balance were improved in CI users when implants were turned on (Cushing, Chia, James, Papsin, & Gordon, 2008). These results support our assertion that while vestibular dysfunction is common among children with profound SNHL who use CI, some of these children also possess a remarkable ability to compensate for their sensory loss (Buchman, Joy, Hodges, Telischi, & Balkany, 2004). Improving our understanding of how children use their sensory systems in the absence of vestibular function may help further our understanding of vestibular physiology and balance and even lead to new targets for rehabilitation.

1.10 Balance in Children with BVL and Bilateral Cochlear Implants

Delay in language acquisition is an obvious and well-known sequelae of hearing loss that was, unfortunately, a common indicator of deafness prior to the institution of newborn hearing screens. Delay in motor function has long been suspected in children with hearing loss, yet it remains almost unrecognized in both the lay and medical communities. Unfortunately, many infants go undiagnosed for prolonged periods or are even mislabeled has having “floppy baby syndrome” due to their delayed ability to control their head (Rapin, 1974). Several groups have noted delay in motor skills such as balance and visuomotor skills (Cushing, Chia, James, Papsin, & Gordon, 2008; Kaga, Shinjo, Jin, & Takegoshi, 2008; Livingstone & McPhillips, 2011; Savelsbergh, Netelenbos, & Whiting, 1991; Siegel, Marchetti, & Tecklin, 1991; Wiegersma & Van der Velde, 1983). Kaga et al. observed delays at all major motor milestones. Head control was not achieved until 4-8 months, crawling began at 7-14 months and walking did not appear until 17-27 months in children with vestibular dysfunction, normal inner ear anatomy, and normal intelligence (Kaga, Shinjo, Jin, & Takegoshi, 2008). Delays were even longer in children with labyrinthine anomalies and children with concomitant cognitive delay. Rapin et al. noted that children with hearing loss and decreased or absent caloric response did not sit independently until 6 to 24 months and walking did not start until 10 to 48 months (Rapin, 1974).

Some debate remains regarding the causality of this motor delay in children with hearing loss. Wiegersma and Van Der Velde proposed four possible, likely inter-related, causative factors including: 1) the auditory deprivation itself; 2) a lack of verbal representations of motor skills and verbal-conceptual strategies to support execution; 3) emotional factors such as a lack of self- confidence and parental anxiety; and finally 4) organic factors such as vestibular loss (Wiegersma & Van der Velde, 1983).

As we have noted previously, hearing and vision appear to be two of the first sensory systems to achieve coordinated function (Muir & Field, 1979). Some authors have observed that children who are deaf are slow to react to objects coming from outside of their visual fields, demonstrated by poorer ball-catching abilities and increased reaction times when a ball is thrown from outside of the field of view (Savelsbergh, Netelenbos, & Whiting, 1991). Interestingly, pleasing sounds such as those derived from clapping or drumming may serve to reinforce bimanual coordination

between the upper limbs during development and formulating our understanding of the impact of our actions on objects. In one study, auditory feedback appeared to provide more salient information than appearance changes when infants manipulated objects during play (Perone, Madole, Ross-Sheehy, Carey, & Oakes, 2008). It is postulated that the lack of auditory stimulation during development can lead to deficiencies in motor coordination and planning that in turn set off a cephalocaudal cascade of motor delay.

Alternatively, it has been proposed that rather than failing to develop accurate methods of orienting to sound emitting objects and delay of system coordination, the auditory deprivation resulting from hearing loss can lead to impaired communication skills. As a result this may limit the amount of physical play a developing child has which is important for development of motor coordination (Livingstone & McPhillips, 2011). Livingstone and McPhillips examined balance in three groups of children (normal hearing, hearing loss, and hearing loss with CI) using the M- ABC and a version of the SOT (Livingstone & McPhillips, 2011). Their results suggested that children with hearing loss experienced significant motor deficits that were more pronounced when activities involved multiple sensory systems and may not have been explained by vestibular impairment alone. They felt that this indicated a more global issue regarding the integration of these systems that is, in part, the product of rules learned through play in the environment. Moreover, during mastery of complex tasks, motor function is intimately associated with language. In early stages, hearing learners are able to listen to instructions from a teacher without having to take their eyes from their task. In later stages, prior to skill automation, verbal activity supports the execution of the task and learners will even recite steps to themselves as they progress through the actions (Fitts & Posner, 1967; Murphy, 2005). This theory is intriguing but may not fully explain motor delay in children with profound hearing loss who have parents who are also deaf or why delay occurs in children with BVL who receive CI early in life.

Emotional factors may also have an important impact. A review that is worthy of the cultural complexities of the Deaf community and the relationships of children who are deaf and their normal hearing peers is beyond the scope of this thesis. However, authors have noted that social anxiety and poor self-esteem and poor self-efficacy are not uncommon entities in children with hearing loss (Mance & Edwards, 2012). Moreover, parents often feel anxious about their

children who have hearing loss and often experience “difficulty with letting go” (Glover, 2003). Wiegersma and Van der Velde suggest that children under these circumstances may not “perceive the world as [their] rightful playground, nor will [they] view [themselves] as a suitable partner in a group” (Wiegersma & Van der Velde, 1983). It is possible that this may deprive some children with hearing loss from typical motor experiences available to their normal hearing peers.

Finally, a common hypothesis is derived from the well-established association of cochlear and vestibular dysfunction. Studies have reported vestibular dysfunction in children with congenital and early acquired hearing loss have ranged widely from 20 to 70% likely reflecting the heterogeneous nature of this condition and testing of vestibular function (Arnvig, 1955; Buchman, Joy, Hodges, Telischi, & Balkany, 2004; Everberg, 1960; R. Goldstein, Landau, & Kleffner, 1958; Guilder & Hopkins, 2006; F. B. Horak, Shumway-Cook, Crowe, & Black, 1988; S. L. Kaplan, Goddard, Van Kleeck, Catlin, & Feigin, 1981; Rapin, 1974; Selz, Girardi, Konrad, & Hughes, 1996). In a large cohort of CI users, Cushing et al. showed vestibular dysfunction occurred in around 50% of patients with CI (Cushing, Papsin, Rutka, James, & Gordon, 2008; Cushing, Gordon, Rutka, James, & Papsin, 2013). Vestibular dysfunction was not seen across all etiologies of sensorineural hearing loss. Vestibular dysfunction was common in etiologies such as Usher Syndrome type 1, meningitis and children with cochleovestibular anomalies; however, it was relatively uncommon in children with mutations of the GJB2 gene (Cushing, Gordon, Rutka, James, & Papsin, 2013). Even within certain high-risk etiologies, vestibular dysfunction is not seen in all afflicted patients. Wiener-Vacher and colleagues found vestibular dysfunction in 10.5% of children with bacterial meningitis, but half had bilateral vestibular loss while the other half had only unilateral vestibular loss (S. R. Wiener-Vacher, Obeid, & Abou-Elew, 2012). Moreover, in this study the time course of infection relative to the age of independent walking had important motor implications. Children who contracted meningitis prior to learning to walk were delayed for approximately 18 months before taking their first steps (S. R. Wiener-Vacher, Obeid, & Abou-Elew, 2012).

Given the heterogeneity of the population when considering atypical motor behaviour in children with hearing loss, caution must be used when assigning causative factors as confounding factors may exist including concomitant neurological impairment, age at diagnosis and interventions

(D. L. Horn, Pisoni, & Miyamoto, 2006). However, from the view point of the dynamic systems model of motor development, each of these hypotheses is interesting as they affect important components of balance acquisition either by preventing the development of coordinate neuromuscular response to stimuli, interacting with the environment to develop coordinate sensory and motor plans, or simply impairing the development of the individual sensory system (Shumway-Cook & Woollacott, 2007). Clearly, multiple factors are at play in this fascinating area of neuromotor development and further study is required.

1.11 Summary

Bilateral vestibular dysfunction in children has far reaching consequences, ranging from impaired balance and delayed motor development, to spatial memory and learning difficulties. The ability of children to remain upright in the absence of this important sense suggests that they are compensating in some way. However, although children with BVL are able to participate in many common childhood activities, they are not able to do so at the level of their peers. Moreover, clinical balance studies using qualitative balance assessments have demonstrated impaired static and dynamic balance in these children. Taken together, these findings suggest that while children are able to compensate to a degree, compensatory strategies may be limited. Therefore, it is important to gain an understanding of how children with BVL compensate for balance function in order to tailor therapeutic strategies and optimize their ability to function safely in day-to-day life. Also, to date balance assessments have been limited to controlled clinical and research environments for both practical and safety reasons. The lack of sensory distractions in these findings may impact the ability to transfer information from “bench to bedside.” In this study, we make use of a high-fidelity virtual environment in which we could recreate and manipulate the streets of downtown Toronto. This allows us to test balance safely in children with BVL while they experience a more realistic environment. In this way, we hope to answer the following questions:

3) A. Are children with known vestibular and hearing dysfunction able to compensate for balance problems using hearing restored through bilateral cochlear implants? B. Will different kinds of sound (directional vs. non-directional) impact balance differently?

Chapter 2

2 Methods

2.1 Overview

Approval for this study was obtained from the Hospital for Sick Children Ethics Review Board and the Toronto Rehabilitation Institute Research Ethics Board and adheres to the Tri-Council Policy Statement - Guidelines on Research Involving Human Subjects. Written consent and verbal assent was obtained from the guardian and children respectively prior to testing.

2.2 Participants

Fifty-four children (18 bilateral CI users with BVL and 36 typically developing controls) participated in this study. Demographic information for both groups is summarized in table 2.1.

Number of patients 54 Children with Typically BVL developing N=18 N=36 Age at testing, median (range) 13.8(8.6-19.7) 15.7(6.0-18.2) Gender (m:f) 9:9 12:24 Visual correction with glasses 12 (66.7%) 10(27.8%) p=0.006 Participate in team sports 11 (61.1%) 26 (76.5%) p=0.407 Can ride bicycle 14 (77.8%) 34 (97.1%) p=0.087 Table 2.1. Demographic factors for both Children with BVL who use CI and typically developing children

Ages at the time of assessment ranged from 6 to 19.7 years of age. Although the ages did not differ significantly between groups, all measures not scaled for age and gender, were specifically age and gender matched. All children with BVL had profound hearing loss necessitating bilateral cochlear implantation. Implantation occurred in a sequential manner with a median (range) inter-

implant delay of 6.8 (0.9-13.5) years. Implant users received Nucleus 24CA, 24M, 24RCS, and 24RE and one patient received a Med-El device on one side. The median (range) age at first implantation was 2.5 (0.7-7.7) years and 10.3 (1.6-17.7) years at time of the second implant. Information specific to Etiology of SNHL, n(%) children with BVL can be Ushers 6 (33.3%) found in table 2.2. All CI Meningitis 4 (22.2%) Unknown 4 (22.2%) users had total bilateral Cochleovestibular anomaly 3 (16.7%) vestibular loss demonstrated CMV 1 (5.6%) Age at time surgery, median (range), years by absent responses on both First CI 2.5 (0.7-7.7) horizontal canal function Second CI 10.3 (1.6-17.7) Inter-implant delay, median (range), years 6.8 (0.9-13.5) testing (including bithermal Duration of Implant use at time of study, caloric responses, rotational median (range), years First CI 11.8 (7.8-16.3) chair testing and/or video Second CI 4.8 (1.3-6.9) head impulse testing) and Table 2.2. Cochlear Implant User Demographic data saccular function testing using cervical vestibular evoked myogenic potentials. All testing was carried out at the University Health Network’s Centre for Advanced Hearing and Balance Testing. A summary of the individual vestibular testing results can be seen in Appendix 1. The typically developing children were accrued from the patients seen at the Hospital for Sick Children Otolaryngology clinic for reasons other than hearing loss, volunteers who contacted the cochlear implant laboratory with an interest to participate, and from a local community centre. Hearing and balance were presumed normal based on history in the typically developing group. Children were excluded from the study if they had known cognitive or motor deficits or uncorrectable visual loss that might preclude completion of all balance tasks. However, children with BVL were significantly more likely to require glasses to correct their vision than the typically developing group.

Balance was assessed in three ways: traditional BOT-2 scoring, motion capture analysis, and force plates measurements of centre of pressure. These will be outlined in the following sections.

2.3 Subjective Assessment of Static and Dynamic Balance Function: BOT-2 Balance Subtest

Static and dynamic balance was assessed using the balance subtest of the Bruininks-Oseretsky test of motor proficiency 2 (BOT-2) (R. Bruininks & Bruininks, 2005). The BOT-2 is an easy to use, individually administered test that requires minimal equipment making it of practical utility in the clinical setting. It was designed for assessment of balance in children ages 4 through 21 years. The balance subtest measures motor skills that are involved in maintaining posture when standing and walking. It is comprised of nine tasks outlined in table 2.3. Seven of the tasks assess static balance while 2 of the tasks are performed while walking a line. Three of the tasks are performed once with eyes open and once with eyes closed. Stationary tasks are scored by timing the tasks with a stopwatch whereas steps are counted during the walking tasks. The trial is stopped if the patient steps off the line or balance beam, takes their hands off their hips, opens their eyes or puts their foot down in a one-legged stance task. These measurements are used to calculate a raw score ranging from 0 to 37. The patient’s age and gender are then used to determine a scaled score that can be used for comparison. The scaled score (range 1-35) is based on normative data derived from standardization studies involving 1,520 children across the United States (R. Bruininks & Bruininks, 2005). The mean score of the BOT-2 is 15 with a standard deviation of five. With respect to the individual tasks for the BOT-2, for ease of nomenclature throughout the remainder of the text we have grouped the tasks into three groups based on the proportion of those able to achieve a near perfect performance score (9 seconds or greater) in easy, moderately difficult and difficult tasks as seen in figure 2.1. These groupings reflect an arbitrary cut off value and while they do reflect the examiner’s observations made during testing, they are not official cut-offs and used only for descriptive purposes.

Balance Subtests Tasks Max Score Task 1 Standing with feet apart on a line * Eyes Open 10 seconds Task 2 Standing on one leg on a line* Eyes Open 10 seconds Task 3 Walking forward on a line Eyes Open 6 steps Task 4 Standing with feet apart on a line Eyes Closed 10 seconds Task 5 Standing on one leg on a line Eyes Closed 10 seconds Task 6 Walking forward heel-to-toe on a line Eyes Open 6 steps Task 7 Standing on one leg on a balance beam * Eyes Open 10 seconds Task 8 Standing heel-to-toe on a balance beam Eyes Open 10 seconds Task 9 Standing on one leg on a balance beam Eyes Closed 10 seconds Table 2.3 BOT-2 Task Summary and grading scheme. Tasks that are marked by an (*) are performed both with eyes open and closed and will be used for comparison in section 3.2.1

Figure 2.1. Task difficulty defined by the proportion of participants in both groups combined who were able to maintain the standing task stances for 9 seconds or greater.

2.4 Objective Methods of Static and Dynamic Balance Function

The first question we wish to address is: Is the BOT-2 a valid and reliable measure of balance? To do so we will perform the standard BOT-2 tasks while measuring children using quantifiable methods of assessment that include motion capture and force plate analysis.

2.4.1 Motion Capture Analysis

Motion capture analysis was performed using the Phoenix Technology motion capture system (Visualeyez, Phoenix Technology Inc, Burnaby, Canada). Motion capture was used to track motion of the head and trunk. The camera was located at the front of the testing area and aimed downwards such that it was able to capture the entirety of the space. Light emitting diode (LED) markers were placed at the head, sternum and lower abdomen and ankles as seen in figure 2.2. Motion capture data were sampled at 120 Hz. Measurements were made of angular deviations around the pitch and roll axes at the head and trunk segments compared to a neutral standing position measured at the start of each trial. Angular deviations were analyzed looking at maximum pitch and roll angular deviation over the course of the trial as well as the root mean square (rms) error.

Figure 2.2. Position of LED motion capture markers at the head, trunk, and limb positions. At the start of each trial participants stood in a neutral stance facing the front to create a zero line off which angular measurements of the head (middle) and trunk (right) could be made.

2.4.2 Force plate Posturography

Quantification of postural stability necessitates measurement of the centre of pressure, which can be accomplished using force plates. The test environment (Figure 2.3a&b) used in this study was equipped with force plates that allowed measurement of COP as the participant performed the tasks of the BOT-2. Participants were instructed to stand on a 1200x1200 cm force plate (AMTI, Watertown USA) while performing the tasks of the BOT-2. Stationary tasks were performed on a pre-marked line positioned in the centre of the force plate (Figure 2.3b). Postural steadiness was examined using the centre of pressure (COP) calculated from the force plate.

Figure 2.3. The CEAL Street Lab testing environment. A) Top down view of the test area within the Street Lab visual dome seen from above (inset: external view of the dome). B) Testing set up consisted of the standard BOT-2 set with a line (blue) for walking and stand (green box) on force plates (grey boxes). At the outset of each trial the distance required for 6 full steps was determined for each child and marked (blue arrow). Two closed circuit video cameras were in place inside the Street Lab (camera icon) to allow the second iteration of BOT-2 scoring for inter-rater reliability or verification of movements.

MATLAB R2012a was used to compute COP measures of postural steadiness. COP-based measures used for the analysis were the rms of COP excursion and total length of the COP path (COP length) calculated as the sum of the distance between consecutive points measure during each trial divided by the duration of each trial (COP velocity). The CE of the bivariate distribution (COPxi, COPyi) is the ellipse in which 95% of the COP samples are predicted to be enclosed (Figure 2.4). The walking tasks were started from a marked point that was measured out at the start of each trial so that each participant would stop at the same point if 6 successful steps were accomplished. In this work we have decided to focus on the stationary tasks of the BOT-2 as a starting point for comparison to the quantitative measures such as posturography.

Therefore, while reporting of the scaled BOT-2 scores necessitates testing of the two walking tasks, the quantitative measurements reported here will be focused primarily on the stationary tasks of the BOT-2 (Table 2.3).

Figure 2.4. The 95% confidence ellipse between a typically developing child and their age and gender matched peer with BVL in a dynamic visual environement with congruent street sounds. Statokinesograms can be quantified in multiple ways. The red circle circumscribes an ellipse defined by the bivariate distribution of COPxi and COPyi and describes the area in which 95% of the COP samples are predicted to be enclosed.

Questions 2 and 3 seek to determine how children compensate for bilateral vestibular loss in order to balance. In Question 2, we ask if visual input plays a greater than normal role for children with BVL to balance and will this be altered by increasing the complexity of visual information as would be experienced on a busy downtown street? In Question 3, we seek to understand if children with BVL are able to compensate for balance problems using hearing restored through bilateral CI and if so, will different kinds of sound (directional vs. non- directional) impact balance differently? In order to understand this we require a way of assessing balance while being able to manipulate environmental conditions in a standardized fashion; something that is more easily accomplished using virtual reality. Question 2 and 3 will be discussed together as they require a similar set up.

2.5 Stimulus Environment: Street Lab Visual Dome

Whenever feasible, testing conditions should reflect the real world as much as possible. This holds true for balance assessments given the degree of coupling that occurs between the human balance sense and the intimate nature of our interaction with the external environment (Waller & Hodgson, 2013). Balance testing was carried out in the Street Lab Visual Dome located in CEAL in the Toronto Rehabilitation Institute (Figure 2.5a). The Street Lab is a dome-shaped laboratory that houses a large, curved projection screen with a field of view of 240° horizontally and 120° vertically. Six projectors (Eyevis ESP- LED series with LED technology) were used to project the visual image on to the surrounding screen (Figure 2.5b). The visual stimulus consisted of a virtual reality scene simulating a street corner in downtown Toronto (University and Elm, facing east). The picture resolution was 6.5 arcmin/OLP and the scene was created using a customized OpenScene Graph application. In the moving visual scene, cars and pedestrians would pass the in a semi-random pattern. In the static street scene the visual scene was paused and no motion was present. Three-dimensional sound was delivered by 7 speakers located behind the projection screen (Meyersound MP-4XP) and a subwoofer (Meyersound MP- 10XP). The sounds consisted of ambient street sounds including that of passing cars to match the street scene or white noise. The loudness of the sounds was approximately 60 dB. White noise was played through all seven speakers to avoid providing any directional information.

Figure 2.5. StreetLab visual environment. A) The relative position of the participants during the standing trial can be seen in relation to the immersive visual environment. B) A participant stands in tandem stance with eyes open (Task 1). Note the full body hardness worn by the participant that is attached to a safety support system is well out of the way and does not encumber the participant’s movements.

2.6 Testing Protocol

Following consent, children and parents were asked to fill out a short questionnaire to obtain demographic information. Once inside the simulator, children were oriented to Street Lab and the safety harness system, and instructions regarding the test were reviewed. Children wore their CIs during this period and were permitted to ask any questions they wished. Parents were able to watch from a closed circuit camera located outside the street lab or accompany the child into the simulator with the child’s permission.

Children performed the tasks of the BOT-2 under a combination of auditory and visual conditions outlined in Table 2.4 and 2.5 for typically developing children and children with BVL respectively. There were four conditions for typically developing children and six conditions for the children with BVL who performed each of the visual conditions both with implants on and off. The order of the conditions was randomized prior to the start of the experiment using a random number generator (www.random.org). Each condition took approximately 10-15 minutes

to complete. Children were given seated breaks in between conditions where they were offered water and a videogame to help pass the time and prevent rushing to get the next condition started before they had rested sufficiently. Frequent inquiries were made to determine if the participants were fatigued and wished an additional break but none were required. Two examiners were present during each trial. Trials were recorded by two video cameras located at the back and to the side of the participant. Scoring of the standard BOT-2 test was performed at a later time by an examiner blinded to the participant’s hearing status and environmental condition. Children were instructed to stand up straight facing the front of the test area at the start of each trial to allow recording of the neutral position against which all angular deviations were measured. If children were not able to stand unaided for this portion the examiner was instructed to support the child. The child was then given the opportunity to stabilize and say “Go” when they felt ready for the trial to be started at which point they attempted to remaining in position for as long as possible. The spotter made hand gestures visible to the cameras and external examiner at this point to mark the start of the trial. Children were barefoot and kept hands-on-hips for the duration of a trial. If children were able to complete the task (i.e. remaining in position for 10 full seconds or completing 6 steps) they moved on to the next task as per the standard BOT-2 protocol. Children who were unable to achieve the maximum score on their first attempt were given two additional trials. Practice attempts are not offered in the standard BOT-2 protocol. Between tasks the examiner would stand facing the participant and demonstrate each task. The instructions were scripted for each child and each trial. Verbal instruction was kept to a minimum but repeated regardless if implants were on or off. Once the participants indicated they understood the task, the trial was started as discussed above.

Auditory Input Congruent White Street Noise Noise Dynamic Street A B Scene Visual Input Static Street C D Scene Table 2.4. Sensory conditions for normal hearing children

Auditory Input Congruent Street Implants White Noise Off Noise Dynamic Street A E B Scene Visual Input Static Street C F D Scene Table 2.5. Sensory conditions for children with BVL. Note that there are two additional conditions (E and F) in this protocol as children with BVL were also tested with implants on and

off.

All children wore a full body climbing harness inside Street Lab that was suspended from a single point harness system on the ceiling (Figure 2.5a&b). A seat belt type cord was connected to the back of climbing harness to avoid causing any hindrance to movement and provided little if any somatosensory information. In this way children were able to achieve maximum excursions without intervention from the examiner or risk of injury.

2.7 Data and Analysis

Angular deviations and force plate recordings were processed and analyzed using MATLAB R2012a. Statistical analysis was performed using SPSS Statistics 22 (IBM). Normality was assessed visually using histograms when possible and if necessary statistical assessments were performed as well. Exploratory statistics in SPSS were used to confirm normalcy making use of the Shapiro-Wilks test (α=0.05).

Repeated measures analysis of variance (ANOVA) was used to compare BOT-2 scores and quantitative measurements across conditions. The design of the ANOVA was tailored to the particular question. When comparing task difficulty by one and two footed tasks a 3-4 (task) x 2(group) mixed factorial ANOVA was used. The impact of vision on balance (measured by postural and kinematic measures) was compared using a 2 (eyes open vs eyes closed task) x 2 (group) mixed factorial ANOVA. The impact of the visual environment on balance was assessed by comparing balance only in the tasks where eyes were open (4 tasks: tandem stance on a line, one-foot on a line, one-foot on a beam, tandem stance on a beam) using a two-way [visual environment (2)]x[task (4)] repeated measures ANOVA. The impact of CI status on balance was compared by balancing with implants on and off in children with BVL. Since this group had significant difficulties with balance in the one footed stance tasks, two-footed and one-footed

stance tasks were compared separately. For two-footed tasks a two way [(implant status (2)]x[two-footed task (3)] repeated measures ANOVA and for one-footed tasks a two way [(implant status (2)]x[one-footed task (4)] repeated measures ANOVA were used for comparison. The impact of the sound environment (directional vs. non-directional sound) was tested in a similar fashion. A two way [(sound environment (2)]x[two-footed task (3)] repeated measures ANOVA or two way [(sound environment (2)]x[one-footed task (4)] repeated measures ANOVA are reported below each set of tasks grouped based on stance as previously described. Chi-square of Fischer’s exact tests were used for comparing dichotomous variables were applicable (i.e. if any observed values were less than 5).

No data were deleted as a result of being defined as an outlier at any time. However, in a number of instances, technical difficulties relating to the equipment malfunction, positioning of the sensors, and/or participant factors (related to blocking sensors by clothing, hair, body habitus, or manual manipulation) resulted in a lack of data for a particular sensor or force plate. Every effort was made to monitor these factors and correct equipment when faulty; however, instances did occur that went unnoticed, leaving missing data. Datacells were not interpolated for statistical analyses but left blank.

Inter-rater reliability was assessed by having two independent reviewers mark the BOT-2. The first rating was performed at the time of the study by a trained rater who watched via monitor outside the simulator. The second rating was performed by independent rater who had access to video recordings taken from two angles(Figure 2.3b): from the back (full length view from head to feet) and from the side (full length view from head to feet and entire length of walking course) so that the whole participant could be observed during the entirety of the balance task. The cohen’s Kappa was used to assess agreement between raters. Inter-rater reliability was interpreted as 0.0 to 0.2 indicating slight agreement, 0.21 to 0.40 - fair agreement, 0.41 to 0.60 - moderate agreement, 0.61 to 0.80 - substantial agreement, and 0.81 to 1.0 indicating almost perfect or perfect agreement (Landis & Koch, 1977). Agreement was assessed between both the total BOT-2 score and each individual task by comparing the maximum time to fall or number of steps that is used to generate the total score upon which the scaled score is calculated.

To investigate known group validity performance on the clinical and quantitative measures were compared using independent samples student’s T tests or Mann-Whitney U tests if the data was not normally distributed. The effect size was determined by calculation of the Cohen’s d statistic. As suggested by Cohen, effect sizes of 0.2, 0.5 and 0.8 were considered as small, moderate, and large respectively in size (J. Cohen, 1988). Convergent validity was assessed by examining correlations between clinical and quantitative measures using Pearson correlation and presented in a multitrait-multimethod matrix format (De Kegel et al., 2010; Streiner & Norman, 1989). The 95% confidence intervals for all correlation coefficients were calculated. The strength of the correlation coefficient was determined as follows: 0.00 to 0.25 indicating little to no correlation, 0.26 to 0.49 – low correlation, 0.5 to 0.69 – moderate correlation, 0.7 to 0.89 – high correlation, and 0.9 to 1.0 indicating very high correlation (Domholdt, 2000).

Chapter 3

3 Results

3.1 Validity and Reliability of BOT-2: Balance Subtest in Detecting Balance Dysfunction in Children

The BOT-2 is an excellent clinical tool that requires children to utilize various sensory and motor strategies to accomplish tasks of increasingly constrained balance. However, as we have discussed, ultimately children are provided with a single score and although a child may have significant difficulty with task, they may still achieve a normal BOT-2 scaled score if they are able to struggle through a task to its completion. Comparing the BOT-2 to quantitative analysis could lend insight into what a particular score may mean. Moreover, understanding differences in postural control and body movements measured by force plates and motion capture during these tasks could be of future use in designing therapeutic strategies that focus on particular aspects of postural control. In order to assess the validity of the BOT-2 we will compare it to two quantitative measures, posturography and in their abilities to discern two known groups (De Kegel et al., 2010). Next we will investigate the convergent validity of the BOT-2 with our quantitative measure to determine whether measures of postural sway obtained during the standing trials can predict or explain functional performance in children.

3.1.1 Inter-Rater Reliability

The BOT-2 was evaluated at two time points and the agreement between individual raters was assessed. The BOT-2 scaled score demonstrated substantial agreement between raters, kappa = 0.66 (Table 3.1). The individual tasks displayed a range of agreement strengths depending on the task, spanning from fair to substantial. The walking tasks showed the greatest agreement with kappa values greater than 0.7. Substantial agreement was also seen in the tandem and one-legged stance tasks (tasks 1 and 3) with eyes open and the tandem stance with eyes closed standing on the floor (task 4). Less agreement between raters was found when raters assessed the moderately difficult tasks where vision was limited or somatosensory input was constrained by the balance beam (task 6, 7, and 8). Interestingly, for the most challenging task, during which falls were not

subtle or unexpected, agreement between raters improved slightly compared to the other difficult tasks (kappa 0.33-0.39) to moderate in strength (kappa = 0.52).

Kappa 95% Confidence Interval sig BOT-2 scaled score 0.66 0.58-0.73 <0.0001 Individual Task Task 1 0.68 0.55-0.81 <0.0001 Task 2* 0.79 0.69-0.89 <0.0001 Task 3 0.63 0.53-0.72 <0.0001 Task 4 0.62 0.54-0.71 <0.0001 Task 5* 0.78 0.68-0.88 <0.0001 Task 6 0.33 0.22-0.29 <0.0001 Task 7 0.39 0.33-0.45 <0.0001 Task 8 0.33 0.28-0.38 <0.0001 Task 9 0.52 0.45-0.59 <0.0001 *compared by step number, all other tasks were compared by time to fall (s) Table 3.1: Inter-rater reliability was assessed looking at both the BOT-2 overall scaled scores and the individual time to fall measures.

3.1.2 Known Group Validity

The BOT-2 score was able to detect a difference between the two groups with a large effect size (d= 4.94) (Figure 3.1). This is in line with previous studies that have shown a significant impairment in static and dynamic balance in children with BVL using this clinical measure (Cushing, Chia, James, Papsin, & Gordon, 2008). Table 3.2 compares the balance performance of the typically developing children to participants with known BVL and CI during the three, two-footed tasks. One- footed task results for each group are Figure 3.1. BOT-2 scaled score results for the displayed similarly in table 3.3. Our second two groups of children, typically developing clinical measure, the time to fall, was (red) and children with BVL who use CI (blue). Balance was significantly worse in children with considered a surrogate of the BOT-2 for task- BVL when balance was measured by the BOT-2.

by-task comparison and for comparison to the quantitative measures. The time to fall differed significantly for all the stationary tasks of the BOT-2 except for the first task of the BOT (two feet on a line, eyes open) which the majority (56%) of children with BVL were able to accomplish in its entirety and 67% were able to maintain stance for 8 seconds or longer.

Posturography was compared in three ways: the COP rms, the COP velocity, and the 95% confidence ellipse. COP rms and COP velocity measures were able to detect a large and significant difference between known patient groups in all tasks in all but the first and last tasks where the effect size was only moderate. The 95% confidence ellipse was able to detect a significant difference between the two groups in all but the last task of the BOT (one leg on a balance beam with eyes closed), for which children in both groups consistently had the most difficulty with.

Motion capture analysis did not consistently detect a difference between groups. In table 3.2, significant differences were seen with moderate to large effect sizes in all three tasks based on a two-footed stance: task 1 (two feet on a line, 8 of 8 measures detected a difference), task 4 (two feet on a line with eyes closed, 8 of 8 measures detected a difference), task 8 (two feet on a balance beam, 7 of 8 measures detected a difference). Overall, motion capture analysis was less consistently able to detect differences in head and trunk angular measurements in one-footed tasks (Table 3.3). In the easiest of the one-foot stance tasks, significant differences with moderate to large effect sizes were seen in 6 of 8 measurements with only the two head pitch measurements not reaching significance. Fewer tasks were able to detect significant differences when vision was removed by closing the eyes; however, large differences in deviations in the “roll plane” measured at the head and trunk were still apparent. When vision was restored but somatosensory input was constrained by a balance beam, only trunk roll angles differed significantly between the groups with a large effect. No significant differences were detected by any of the measurements in the most difficult task (task 9, one foot on a balance beam, eyes closed).

d 2.5 1.9 1.5 1.5 0.8 0.5 1.1 1.1 1.0 0.4 1.0 1.2 p 0.2 0.03 0.01 0.003 0.004 0.005 0.004 0.002 <0.0001 <0.0001 <0.0001 <0.0001 CI userCI 4.4(0.8) 9.3(2.4) 8.4(1.7) 9.3(1.8) 3.7(0.6) 7.2(1.3) 21.7(4.0) 19.1(3.8) 13.8(2.2) 132.7(20.9) 613.5 (115.3) 613.5(115.3) 767.8(173.8) 10(0) Normal 5.4(1.4) 6.2(1.4) 2.8(0.6) 3.5(0.6) 1.9(0.2) 6.3(1.5) 2.4(0.5) 10.7(3.0) 18.8(2.9) 18.4(6.9) Task 8: Two feet on abeameyes - feet on open 8:Two Task 113.7 (16.6) 113.7

d 1.2 1.6 1.3 1.2 1.5 1.5 1.0 1.0 1.4 1.3 1.3 1.3

p 0.01 0.01 0.001 0.001 0.002 0.001 0.001 0.001 <0.0001 <0.0001 <0.0001 <0.0001 statistic. COP = center of pressure, RMS = root mean square, 95% CE = 95% 95% CE square, of pressure, RMS mean = root = center COP statistic.

d CI userCI 7.2(0.7) 8.0(1.2) 6.5(1.8) 7.8(1.3) 2.9(0.4) 5.0(0.9) 11.5 (2.1) 11.5 21.2(3.7) 16.0(4.2) 77.1(12.6) 327.2(62.7) 341.7(98.0) Task 4: Two feet on a line - eyes- closed aline feet on 4:Two Task 10(0) Normal 4.5(0.6) 2.4(0.4) 3.2(0.8) 1.2(0.3) 1.2(0.2) 3.3(0.8) 1.4(0.3) 2.5(0.3) 18.3(1.7) 14.0(1.8) 102.1(7.5) d* 0.2 0.8 0.4 0.6 0.8 0.7 0.8 1.0 0.9 0.8 1.0 1.2 p 0.6 0.04 0.05 0.02 0.01 0.04 0.03 0.01 0.00 <0.0001 <0.0001 <0.0001 CI userCI 9.6(1.7) 8.4(2.8) 8.2(2.0) 3.8(0.8) 4.4(1.1) 2.1(0.9) 5.7(1.1) 2.9(0.6) 13.9(3.6) 51.0(16.7) 128.1(71.2) 385.0(250.1) Task 1: Two feet on a line - eyes- open aline feet on 1:Two Task 10(0) Normal 5.5(1.3) 2.6(0.6) 3.0(0.7) 1.2(0.2) 1.9(0.4) 0.9(0.2) 2.0(0.5) 0.9(0.2) 12.8(0.9) 79.5(7.9) 5.4(0.82) : Known group validity results for two-footed tasks. *Effect size is shown by the Cohen’s is shownCohen’s size by the tasks. *Effect for two-footed results Known: group validity

rms Clinical Skills Skills Clinical fallto Time Posturography rms COP velocity COP 95%CE capture Motion max HP rms HP HRmax HRrms max TP rms TP max TR TR 3.2 Table roll. = trunk TR roll, HR = head pitch, = trunk TP pitch, = head HP ellipse, confidence

d 3.1 0.5 0.9 0.6 0.1 0.0 0.3 0.1 0.4 0.0 0.6 0.1 p 0.1 0.8 1.0 0.4 0.8 0.3 0.9 0.1 0.4 0.012 <0.0001 <0.0001 closed CI userCI 2.0(0.4) 7.5(1.8) 5.7(1.3) 8.4(1.6) 4.1(0.7) 6.1(0.8) 11.8 (2.0) 11.8 17.9(3.7) 10.9(1.1) 166.5(28.1) 1181.9 (371) 1181.9 742.1(209.8) Normal Task 9: One foot on abeameyes - on foot 9:One Task 8.3(0.6) 7.6(1.0) 5.3(0.9) 4.2(0.7) 7.5(1.2) 11.6 (2.4) 11.6 18.9(3.2) 15.1(3.0) 17.0(3.1) 55.7(22.4) 293.7(124) 215.4(28.1) d 2.2 1.3 0.9 0.8 0.6 0.2 0.7 0.6 0.6 0.6 0.7 0.8 p 0.1 0.5 0.1 0.1 0.1 0.01 0.03 0.04 0.05 0.04 <0.0001 <0.0001 CI userCI 4.9(0.8) 8.0(1.7) 6.3(1.0) 3.4(0.6) 7.5(0.9) 22.8(4.5) 16.6(2.3) 10.4(2.1) 18.0(2.1) 105.3(23.3) 466.9(129.3) 350.4(138.9) 10(0) Normal 6.2(1.8) 9.3(2.5) 3.9(1.1) 5.9(1.7) 2.2(0.4) 4.5(1.1) 21.3(3.9) 12.7(3.2) 10.4(2.0) 116.7 (17) 116.7 33.3(14.0) Task 7: One foot on abeameyes - on foot 7:One Task open d 4.6 2.1 2.1 1.3 0.9 0.7 1.1 1.0 0.4 0.6 0.7 0.9 statistic. COP = center of pressure, RMS = root mean square, 95% CE = 95% confidence ellipse, ellipse, = 95% confidence 95% CE square, of pressure, RMS mean = root = center COP statistic.

d p 0.01 0.06 0.01 0.27 0.07 0.04 0.01 0.001 0.004 <0.0001 <0.0001 <0.0001 closed CI userCI 2.5(0.4) 9.2(2.0) 9.7(1.3) 4.5(0.7) 6.9(1.2) 26.1(4.9) 10.1(1.7) 20.8(4.3) 15.6(3.3) 105.4(13.2) 605.9(82.3) 360.8(92.2) Task 6: One foot on a line - eyes- aline on foot 6:One Task

Normal 9.6(0.4) 5.6(1.6) 6.9(1.8) 3.2(0.9) 7.2(1.9) 2.9(0.5) 7.8(1.7) 3.2(0.7) 11.0 (2.8) 11.0 28.4(3.1) 138.6(14) 41.3 (11.2) 41.3(11.2) d 1.2 1.3 5.1 1.3 0.6 0.2 0.8 0.7 1.1 1.0 0.9 0.8 p 0.0 0.12 0.58 0.03 0.05 0.01 0.01 0.02 0.001 0.001 0.004 <0.0001 open CI userCI 7.2(0.8) 4.2(0.9) 6.3(2.1) 7.4(1.4) 3.2(0.6) 7.3(2.1) 10.7(2.5) 13.5(4.1) 14.4(3.9) 224.9(37) 147.2(39) 60.2 (11.7) 60.2(11.7) Task 3: One foot on a line - eyes- aline on foot 3:One Task 10(0) Normal 9.2(1.0) 6.2(1.2) 3.5(0.8) 3.7(0.9) 1.7(0.4) 2.9(0.4) 1.5(0.2) 3.7(0.9) 2.1(0.5) 15.0(1.9) 88.4(8.7) : Known group validity results for one-footed tasks. *Effect size is shown by the Cohen’s is shownCohen’s size by the tasks. *Effect for one-footed results Known: group validity Clinical Skills Skills Clinical fallto Time Posturography rms COP velocity COP 95%CE capture Motion max HP rms HP HRmax HRrms max TP rms TP max TR rms TR 3.3 Table roll. = trunk TR roll, HR = head pitch, = trunk TP pitch, = head HP

3.1.3 Convergence Validity

The correlation coefficients comparing the different clinical test measures (BOT-2 scaled score and time to fall), the different posturographic assessment methods, and the motion capture analyses are depicted in multitrait-multimethod matrices for each task of the BOT-2 (Table A.2- A.8) for typically developing children, and Table A.9-A.15 for children with BVL) (Streiner & Norman, 1989). The number of measures that correlated significantly with one another differed between the two groups of children. On the whole, more statistically significant correlations between the various postural measurements were seen for children with BVL when the tasks were easy. Conversely, for typically developing children, the measures correlated significantly more often when the tasks were more challenging, reflecting a spread in their abilities to successfully accomplish the tasks when sensory inputs were limited. In general, as the BOT-2 scores and time to fall increased there was a reduction in the COP rms, COP velocity and 95% confidence ellipse, and the angular measurements of the head and trunk decreased. However, the statistical significance and strength of these correlations varied both between tasks and groups.

BOT-2 Score vs. quantitative measures of postural control

The BOT-2 score did not correlate significantly with any of the posturographic measurements made during the simplest task of the BOT-2 (Table A.2 and A.8). When standing in tandem stance with eyes closed on flat ground (task 3, Figure 3.2a) there were significant, inverse correlations between BOT-2 scaled scores with COP rms and the velocity in children with BVL (Figure 3.2b&c). The 95% confidence ellipse was not significantly correlated with the BOT-2 score for this task (p=0.07) (Figure 3.2d). This correlation was not observed in typically developing individuals. For typically developing individuals, significant correlations between the BOT-2 score and the individual posturographic measures only became apparent as the tasks became more difficult, particularly when standing with only one foot on a balance beam. In task 7, where typically developing children balanced with eyes open on a balance beam, there was a low to moderate correlation between BOT-2 scores and COP rms as well as 95% confidence ellipse (r = -0.56 and r=-0.48, respectively). When task difficulty was increased further by closing the eyes (Task 9, Figure 3.3a), moderate to high strength correlations were seen for all three COP measures and BOT-2 scores (Figure 3.3b-d). That is, in task 9 when typically

developing children balanced on a beam with eyes closed, children who were able to achieve better overall BOT-2 scores tended to move their COP less (decreased rms and 95% confidence ellipse) and more slowly. Only isolated, significant correlations were seen between angular measurements of the head and trunk and BOT-2 scores. No obvious trends were noticeable for either group.

Figure 3.2. Correlation of BOT-2 scores with posturographic measures for task 3. A) Participant stands on one foot with eyes open. Children with BVL whose higher BOT-2 scores tended to have lower COP rms (B) and COP velocity (C) in this task. The correlation between BOT-2 score and 95% confidence ellipse was not significant (D).

Figure 3.3. Correlation of BOT-2 scores with posturographic measures for task 9. A) Participant stands on one foot with eyes closed on a balance beam. Typically developing children who higher BOT-2 scores tended to have lower COP rms (B) and COP velocity (C) in this task and a smaller 95% confidence ellipse (D).

Time to fall vs. quantitative measures of postural control: typically developing children

When the tasks of the BOT-2 were investigated individually for correlations with quantitative measures, not all tasks could be assessed in our typically developing group. Typically developing children were able to achieve the maximum scores on all but the two most difficult tasks. As a result, their time to fall measurements did not have sufficient spread for assessment of correlation with the quantitative measurements. In the two most challenging tasks (task 6 and 9);

however, significant correlations could be detected. When typically developing children stood on one foot on stable ground with eyes closed, increased time to fall correlated highly with decreasing COP velocity (r=-0.88) and 95% confidence ellipse (r=-0.76) (Figure 3.4 f&g). There was only a low strength correlation with reduction in COP rms but this did not reach statistical significance (Table A.5). In this task (one-legged, eyes closed, Figure 3.5a), as time to fall increased the angular deviations measured at the head and trunk decreased. Stronger correlations were seen for head pitch and roll angles (r=-0.85 to -0.9, Figure 3.5b&c) than for trunk angles (r=-0.46 to -0.52, Figure 3.5d&e) in this task. Interestingly, there was a range of segmental movements that were tolerated in the typically developing children who were able to maintain one-legged stance with eyes closed for the full 10 seconds without falling, particularly in the trunk (Figure 3.5d&e). As the task was made more difficult by the addition of a balance beam (Task 9), a significant correlation was seen between time to fall and posturographic measures.

Children in the typically developing group were able to stay upright longer had significantly reduced COP rms and COP velocities. A moderate strength correlation was seen with COP rms (r=-0.63, p=0.01) and a high strength correlation with COP velocity (r=-0.79, p<0.0001). For this task, only a single moderate strength correlation was identified (maximum head pitch) when comparing time to fall and angular measurements at the head and trunk (Table A.8).

Figure 3.4 (Part 1 a&b). Correlations between individual time to fall and posturographic measures (COP rms, COP velocity and 95% confidence ellipse) for both typically developing children (red) and children with BVL who use CI (blue). The results are grouped by task difficulty, easy (A&B), moderately difficult (C, D &E) and difficult (F&G).

Figure 3.4 (Part 2 c-e). Correlations between individual time to fall and posturographic measures (COP rms, COP velocity and 95% confidence ellipse) for both typically developing children (red) and children with BVL who use CI (blue).The results are grouped by task difficulty, easy (A&B), moderately difficult (C, D &E) and difficult (F&G).

Figure 3.4 (Part 3 f&g). Correlations between individual time to fall and posturographic measures (COP rms, COP velocity and 95% confidence ellipse) for both typically developing children (red) and children with BVL who use CI (blue).The results are grouped by task difficulty, easy (A&B), moderately difficult (C, D &E) and difficult (F&G).

Figure 3.5. Correlation between trunk movement and time to fall for task 6. A) Participant stands on one leg with eyes closed. Typically developing children who were able to maintain stance longer tended of have reduced maximum head pitch and roll (B), reduced head pitch and roll rms (C) measurements. Maximum trunk pitch and trunk pitch rms were also reduced in children who were more successful in this trial (D) but no correlation was seen for trunk roll measurements (E).

Time to fall vs. quantitative measures of postural control: children with BVL

Given the greater range of balance skills in the group of children with BVL, more time to fall information was available for evaluation. In the easy and moderately difficult tasks (Task 1, 3, and 4), an increasing time to fall was highly correlated with improved postural stability demonstrated by reductions in posturographic measurements (Figure 3.4). Amongst these tasks, stronger correlations were observed when the difficulty of the tasks were increased slightly by constraining somatosensory information (standing on one foot, r=-0.77 to 0.91, p<0.0001) or reducing vision (two feet on a line, eyes closed, r=-0.66 to 0.83, p<0.02) compared to the

simplest task where participants stood with two feet on a line with eyes open (r=-0.61 to 0.64, p=0.01). When somatosensory information was further constrained by the addition of a balance beam the strength of the correlations decreased, with only moderate correlations seen when patients stood with one foot on a balance beam (Task 7) (r=-0.55 and 0.61, p<0.04) and only the COP velocity correlated with time to fall when patients stood on a balance beam with two feet and eyes open (Task 8) (r=-0.76, p<0.0001). Interestingly, contrary to the observations made in the typically developing group, no significant correlations were noted in either of the difficult one-footed tasks when eyes were closed (Task 6 and 9). Overall, the COP velocity followed by the COP rms were the most consistently correlated with time to fall and these associations ranged from moderate to high (r=-0.61 to 0.83). Significant correlations between time to fall and angular deviations at the head and trunk were only observed infrequently in the easier balance tasks. The most consistent correlation was between increasing time to fall and reduced maximum head pitch angles, but this was only moderate in strength (r=-0.50 to 0.55, p<0.05) (Table A.9- A.15).

The impact of vestibular dysfunction on balance and postural control

These analyses reveal interesting differences between how children with BVL and their typically developing peers move while attempting to maintain static balance with increasingly difficult sensory and motor constraints. Using the clinical measure, we observed a disparity between the biological ages of the participants and their equivalent balance age. The BOT-2 manual provides tables by which equivalent balance ages can be determined, that is the age to which their balance abilities best correspond (R. Bruininks & Bruininks, 2005). Interestingly, while the biological ages of our two groups were similar there was a difference in the equivalent balance age between groups (Figure 3.6). The median age of the typically developing group was 13.8 years and did not differ significantly from the equivalent balance age (15.2 years) derived from the manual (p=0.08). However, the median equivalent balance age for children with BVL was 4.5 years of age and this was significantly lower than their biological age (14.3 years) when compared by Mann-Whitney U test.

The quantitative measures suggested that postural control was impaired in children with BVL and CI using posturography to measure their COP. Significantly greater variability was seen in

COP position as measured by the rms in all tasks when compared by a 7 (task) x 2 (group) mixed factorial ANOVA (Figure 3.7). The amount of variability increased significantly with the difficulty of the task (p<0.0001) and this effect was more pronounced in children with BVL (task*group, p= 0.007). Using an independent samples t-test, it appears that the COP rms was greater in children with BVL even when no fall was observed for two more difficult two-footed tasks (4 and 8) and for the simplest one-footed task with eyes open (task 3) (Figure 3.8). Similarly, the velocity of the COP was significantly greater for all tasks (Table 3.2 and Table 3.3). The COP velocity increased with increasingly constrained balance tasks (p=0.013). A trend towards an interaction of this task effect with group was seen with COP velocity increasing to a greater extent in children with BVL compared to their typically developing peers as tasks became more difficult (task*group, p = 0.057). Figure 3.9 demonstrates that even when children with BVL did not fall they had significantly greater COP velocities than their typically developing peers. Although the majority of typically developing individuals COP’s moved more slowly than the BVL group, in figure 3.9 there are two typically developing children in task 1 and three typically developing children in task 3 that moved faster than the majority of children with BVL. These individuals were younger (age range 7-10) than the median age of the typically developing group (13.8 years, p=0.044). The area of the 95% confidence ellipse was significantly greater for children with BVL compared to their typically developing peers for all tasks, except the most challenging task, one foot on a balance beam with eyes open. The 95% confidence ellipse increased significantly as the task difficulty increased (p<0.0001) and this interacted significantly with the group type (task*group, p=0.014).

Figure 3.6. Children with BVL who used CI had significantly lower equivalent balance ages compared to their actual ages whereas the equivalent balance age for typically developing children reflected their actual ages more closely.

Figure 3.7. COP rms differed significantly between typically developing children (blue) and children with BVL who use CI (red) for all standing tasks of the BOT-2.

Figure 3.8. COP rms compared between typically developing children and children with BVL who did not fall in three tasks. A) Task 3: one foot with eyes open. B) Task 4: two legged stance with eyes closed. C) Task 8: two legged stance on a balance beam with eyes open.

Figure 3.9. COP velocity compared between typically developing children and children with BVL who did not fall in four tasks. A) Task 1: two-legged stance with eyes open. B) Task 3: one foot with eyes open. C) Task 4: two legged stance with eyes closed. D) Task 8: two-legged stance on a balance beam with eyes open.

When using both feet to stabilize, children with BVL had greater angular deviations at both the head and the trunk than their typically developing peers, regardless of whether they stood with eyes open or closed or if they stood on solid ground or a balance beam demonstrated (Table 3.3). Although head and trunk pitch angles of the children with BVL over the course of the trial were greater than the typically developing participants (head pitch rms, p=0.005 and trunk pitch rms, p<0.001) this was not related to the particular balance task when compared by a 3 (task) x 2 (group) mixed factorial ANOVA (Figure 3.10a&b). However, roll angles were significantly greater as the task difficulty increased in children with BVL (Figure 3.10c&d). One-footed tasks are compared separately in figure 3.11 using a 4 (task) by 2 (group) mixed factorial ANOVA. As we saw in table 3.3, head and trunk movements were significantly greater in the CI user group in the simplest one-legged task and progressively fewer differences were seen as the sensory inputs to balance became increasingly constrained. Head and trunk pitch rms increased with increasing task difficulty while standing on one foot but this did not interact significantly with the group for either body segment (Task*group, p=0.33). An interesting pattern emerged in the roll angle rms (Figure 3.11c&d). Roll angle variability at the head and trunk was uniformly large across all tasks in children with BVL. However, the amount of head and trunk roll variability increased progressively for typically developing children as the tasks became more difficult, eventually approximating the values observed for children with BVL in the most difficult one legged task (eyes closed on a balance beam).

Figure 3.10. Comparison of head and body movement for two foot tasks. Comparison between typically developing children (red) and children with BVL who use CI (blue). Measureable differences were observed for head pitch rms (A), trunk pitch rms (B), head roll rms (C), trunk roll rms (d). Statistical results for a 3 (task) x 2 (group) mixed factorial ANOVA are reported below for each segment. In each figure the x-axis shows: Task 1: two feet on a line; Task 4: two feet on a line, eyes closed; Task 8: two feet, eyes open, on a balance beam.

Figure 3.11. Comparison of head and body movement for one-footed tasks. Comparison between typically developing children (red) and children with BVL who use CI (blue) at the head pitch rms (A), trunk pitch rms (B), head roll rms (C), trunk roll rms (d). Statistical results for a 4 (task) x 2 (group) mixed factorial ANOVA are reported below for each segment. In each figure the x-axis shows: Task 3: one foot, eyes open on a line; Task 6: one foot, eyes closed, on a line; Task 7: one foot, eyes open, on a line; Task 9: one foot, eyes closed, on a balance beam.

Summary of Aim 1:

In summary, here we see that the BOT-2 overall score demonstrates substantial inter-rater reliability. However, some degree of variation was seen in the reliability between individual task evaluations with the walking tasks having better agreement between raters than standing tasks and easier tasks better than more difficult tasks. Assessment of known-group validity suggests that the BOT-2 is good at differentiating between groups with the largest effect size of our measures. Similarly, time to fall and posturographic measures were also good at differentiating between participants with and without vestibular loss. COP rms and COP velocity were able to detect significant differences between groups; however, the 95% confidence ellipse was not able to detect differences in all tasks, particularly as they became more difficult. The 95% confidence ellipse falls prey to artifact when the task durations are shorter and therefore have fewer data points available to calculate its dimensions. As such, for the remainder of this work, we will focus on the COP rms and COP velocity for quantification of the COP. The angular measurements with motion capture analysis were less effective at differentiating groups. Angular deviations were consistently different in the two-footed tasks; however, in the one-footed tasks, fewer differences were seen as the tasks became more difficult. Interestingly, more significant correlations between the various postural measures were seen for children with BVL when the tasks were easy. Conversely, for typically developing children, the measures correlated significantly when the tasks were more challenging. This reflected a ceiling effect that occurred in the easier tasks in which the typically developing children were uniformly able to achieve a maximum score. In general, as the BOT-2 scores and time to fall scores increased, there was a reduction in the COP rms, velocity, 95% confidence ellipse and the angular measurements at the head and trunk. However, the statistical significance and strength of these correlations varied both between tasks and groups. In the following sections we will now assess the role of vision and audition on balance in children with BVL.

3.2 Impact of Vision on Balance in Children with BVL

We observed striking deficits in static and dynamic balance measured by our clinical and quantitative measures in children with BVL compared to their typically developing peers. Given the apparent disparity between these measures and their day-to-day functional abilities, we wished to determine if these children were using vision to help improve their balance. We will investigate the impact of vision on balance in children with BVL in the following section.

3.2.1 Does Vision Play a Greater than Normal Role in Balance in Children with Bilateral Cochleovestibular Loss than their Typically developing Peers?

A number of BOT-2 tasks are repeated with eyes open and closed (Table 2.3) allowing examination of the impact of vision on those static balance stances. Typically developing children were able to maintain an upright stance longer in all tasks, with and without vision (Figure 3.12). The impact of vision on the ability to maintain a static stance with either two feet or one foot on stable ground was greater for children with BVL than for their typically developing peers when compared by a 2 (eyes open vs eyes closed task) x 2 (group) mixed factorial ANOVA (vision*group, p=0.001 and p<0.0001 respectively) (Figure 3.12a&b). However, when the one-footed task was made even more difficult with the addition of a balance beam, this interaction was lost (Figure 3.12c).

Postural stability measured by the COP was significantly better in both groups when all three of the paired tasks were performed with eyes open (Figure 3.13). The COP moved significantly faster when eyes were closed in both groups and this effect appeared to be fastest in children with BVL compared to their typically developing peers (vision*group, P<0.0001) for the two- footed and one-footed stances performed on stable ground (Figure 3.13a&b). The variability of the participants COP was also significantly greater in children with BVL compared to their typically developing peers when eyes were closed (Figure 3.13d&e). While both measures of postural stability were improved when children attempted to stand on a balance beam with eyes open compared to balancing while eyes were closed (p=0.006), no interaction was seen between

group and vision when balance was compared by a 2 (eyes open vs eyes closed task) x 2 (group) mixed factorial ANOVA (Figure 3.13c&f).

The impact of vision on pitch and roll angular deviations differed based on the type of task. In Figure 3.14 and Figure 3.15, it appears as though both the maximum head pitch (Figure 3.14a) and roll (Figure 3.15a) angles were greater when eyes were closed and that this effect interacted significantly with the group type when compared by a 2 (eyes open vs eyes closed task) x 2 (group) mixed factorial ANOVA (vision*group, p= 0.041 and p=0.02, respectively). As the tasks became more difficult by standing on one foot, a significant improvement was seen for both the maximum head pitch and the variability of the head pitch over the course of the trial represented by the rms (Figure 3.14b&e) but no difference was seen in head roll (Figure 3.15b&e). Although it appeared that the change in variability of both head pitch and roll was greater in children with BVL, this did not reach significance. While attempting the most difficult tasks on the balance beam, head movements in either plane were not affected by the presence or absence of vision (Figure 3.14c&f, Figure 3.15c&f). Segmental measurements of the trunk appeared to follow a similar pattern. Maximum trunk pitch angles were only altered by vision in the easier tasks (two foot stable surface, p=0.004 and one-foot stable surface, p=0.016) (Figure 3.16a&b). Trunk pitch angles over the course of the trial as measured by the rms did not appear to be affected by vision (Figure 3.16 d-f). As seen in head roll measurements, an interaction with group type was seen (vision*group, p=0.006) when looking at the amount of maximum trunk roll in tandem stance (Figure 3.17a), but unlike head roll angles, the interaction effect was maintained with trunk roll angles over the course of the trial being significantly greater for children with BVL when eyes were closed in tandem stance (Figure 3.17d). Vision did not appear to have the same effect on roll angles when children attempted to stand on one foot on stable ground. Roll angles at the head or trunk (maximum roll angle or roll angle rms) did not differ significantly with eyes open or closed for both groups (Figure 3.17b&e). When somatosensory input was limited further by having participants stand on one foot on a balance beam angular measurements at the head and trunk increased (Figure 3.14-3.17c&f). In children with BVL, a reduction in head and trunk angles were seen for all measures except trunk pitch rms (Figure 3.17f). Except for trunk pitch rms, a statistically significant change in balance was not observed in any of the other measures. However, an interaction was between presence of visual input and group was seen for the head roll (maximum angle) and trunk roll (maximum

angle and rms). For the normal hearing group an apparent increase in angular deviations of the head and trunk did appear to occur when eyes were closed. The segmental movements of the normal hearing children were therefore assessed separately to determine the impact of vision on this difficult task (Task 7 vs Task 9). A statically significant difference was seen in the amount of maximum head roll angles (p=0.02) and the head roll rms (p=0.022). No statistically significant differences were seen for head pitch. The trunk roll angle rms increased with eyes closed and this approach statistical significance (p=0.058). The maximum trunk pitch and the variability of the trunk pitch angles increased when the participants closed their eyes.

Figure 3.12. Impact of vision on the duration of stance. Paired tasks (done with eyes open and eyes closed were compared by time to fall between typically developing children (red) and children with BVL who use CI (blue). A) Task 1: two feet, eyes open on a line vs. Task 4: two feet eyes closed, on a line. B) Task 3: one foot, eyes open, on a line vs. Task 6: one foot, eyes closed, on a line. C) Task 7: one foot, eyes open on a balance beam vs. Task 9: one foot, eyes closed, on a balance beam. Statistical results for a 2 (eyes open vs eyes closed task) x 2 (group) mixed factorial ANOVA are reported below for each set of tasks.

Figure 3.13. Impact of vision on postural control. Paired tasks (done with eyes open and eyes closed were compared by COP velocity (A-C) and COP rms (D-F) between typically developing children (red) and children with BVL who use CI (blue). The mean change in COP rms or velocity for each pair of tasks is seen to the right of each histogram. A &D) Task 1: two feet, eyes open on a line vs. Task 4: two feet eyes closed, on a line. B&E) Task 3: one foot, eyes open, on a line vs. Task 6: one foot, eyes closed, on a line. C&F) Task 7: one foot, eyes open on a balance beam vs. Task 9: one foot, eyes closed, on a balance beam. Statistical results 2 (eyes open vs eyes closed task) x 2 (group) mixed factorial ANOVA are reported below for each set of tasks.

Figure 3.14. Impact of vision on maximum head angles. Paired tasks (done with eyes open and eyes closed were compared by the maximum head pitch angle (A-C) and maximum head roll angle (D-F) between typically developing children (red) and children with BVL who use CI (blue). The mean change in head pitch for each pair of tasks is seen to the right of each histogram. A&D) Task 1: two feet, eyes open on a line vs. Task 4: two feet eyes closed, on a line. B&E) Task 3: one foot, eyes open, on a line vs. Task 6: one foot, eyes closed, on a line. C&F) Task 7: one foot, eyes open on a balance beam vs. Task 9: one foot, eyes closed, on a balance beam. Statistical results for a 2 (eyes open vs eyes closed task) x 2 (group) mixed factorial ANOVA are reported below for each set of tasks.

Figure 3.15. Impact of vision on head angle rms. Paired tasks (done with eyes open and eyes closed were compared by the head pitch angle rms (A-C) and head roll angle rms (D-F) between typically developing children (red) and children with BVL who use CI (blue). The mean change in head roll for each pair of tasks is seen to the right of each histogram. A &D) Task 1: two feet, eyes open on a line vs. Task 4: two feet eyes closed, on a line. B&E) Task 3: one foot, eyes open, on a line vs. Task 6: one foot, eyes closed, on a line. C&F) Task 7: one foot, eyes open on a balance beam vs. Task 9: one foot, eyes closed, on a balance beam. C & F) Statistical results for a 2 (eyes open vs eyes closed task) x 2 (group) mixed factorial ANOVA are reported below for each set of tasks. Typically developing children were compared separately in the most difficult tasks using a pair-sample t-test *p=0.02; **p=0.002.

Figure 3.16. Impact of vision on trunk pitch. Paired tasks (done with eyes open and eyes closed were compared by the maximum trunk roll angle (A-C) and trunk roll angle rms (D-F) between typically developing children (red) and children with BVL who use CI (blue). The mean change in trunk pitch for each pair of tasks is seen to the right of each histogram. A &D) Task 1: two feet, eyes open on a line vs. Task 4: two feet eyes closed, on a line. B&E) Task 3: one foot, eyes open, on a line vs. Task 6: one foot, eyes closed, on a line. C&F) Task 7: one foot, eyes open on a balance beam vs. Task 9: one foot, eyes closed, on a balance beam. Statistical results for a 2 (eyes open vs eyes closed task) x 2 (group) mixed factorial ANOVA are reported below for each set of tasks.

Figure 3.17. Impact of vision on trunk roll. Paired tasks (done with eyes open and eyes closed were compared by the maximum trunk pitch angle (A-C) and trunk pitch angle rms (D-F) between typically developing children (red) and children with BVL who use CI (blue). The mean change in trunk roll for each pair of tasks is seen to the right of each histogram. A &D) Task 1: two feet, eyes open on a line vs. Task 4: two feet eyes closed, on a line. B&E) Task 3: one foot, eyes open, on a line vs. Task 6: one foot, eyes closed, on a line. C&F) Task 7: one foot, eyes open on a balance beam vs. Task 9: one foot, eyes closed, on a balance beam. Statistical results for a 2 (eyes open vs eyes closed task) x 2 (group) mixed factorial ANOVA are reported below for each set of tasks.

3.2.2 Does the Visual Environment Affect Balance in Children?

The visual environment of any child is complex as children move relative to objects and as objects move relative to them. Clinical tests of balance often occur in simple, controlled environments where little if any movement occurs around the child. Large shifts in the visual environment, such as those in the moving-room studies discussed earlier, can profoundly affect posture and balance in children (Butterworth & Hicks, 1977). However, the effects of more subtle visual changes in which objects in the environment are moving are not understood. In the following section, we compare balance in children between two different visual environments: a dynamic visual scene in which cars and pedestrians pass children as they perform balance tasks at a virtual street corner and a static virtual scene where the environmental objects were kept still.

Balance was first compared by overall BOT-2 scaled score (Figure 3.18). Comparison of BOT-2 scaled scores confirmed that participants with normal hearing performed better on the tasks overall than children with BVL regardless of what was happening in the visual environment (p<0.0001). However, balance did not change significantly for either group based on the presence or absence of moving content within the virtual environment. The mean scaled score for typically developing children within the dynamic Figure 3.18. BOT-2 scores compared between visual environment was 18.1 (3.9) and environments. Balance was compared by the composite this did not differ significantly BOT-2 scaled scores while children performed the BOT in a static visual environment when objects in the virtual from their score [17.7 (4.6)] in environment were kept still and in a dynamic visual the static environment when environment where cars and pedestrians moved past the participants. Dashed line represents the standardized examined using a paired t-test normal mean of the BOT-2 (15). (p=0.538). Similarly, Children

with BVL had a mean balance score of 5.2 (1.8) in the dynamic visual environment and 5.5 (2.4) in the static environment (p=0.476).

The influence of the visual scenes on individual tasks of the BOT-2 where eyes were open was compared on the basis of time to fall in figure 3.19 by a two-way (visual environment(2) and task(7) mixed factorial ANOVA. The typically developing children were able to maintain stance for the entire duration of the task and were significantly better than their peers with BVL regardless of the visual environment (task*group, p<0.0001). However, the presence of moving objects in the environment did not appreciably alter the duration children in either group were able to maintain stance in any of the tasks (environment*task*group, p=0.296).

Figure 3.19. Impact of visual environment on time to fall in eyes open tasks. Balance was compared by time to fall while children performed the 4 eyes open tasks (Task 1: two feet on a line, Task 3: one foot on a line, Task 7: one foot on a balance beam, and Task 8: two feet on a balance beam) in a static visual environment when objects in the virtual environment were kept still and in a dynamic visual environment were cars and pedestrians moved past the participants. The typically developing group overlapped at ceiling level in both the static and dynamic VE and so only one line is visible above. Statistical results for between subjects (2) two-way (visual environment(2) and task(7) mixed factorial ANOVA are reported below the figure.

Typically developing children were able to maintain good postural control despite the difficulty of the task and this did not appear to be altered by the visual condition (Figure 3.20a&c). Postural control was influenced by the difficulty of the task in children with BVL when measured by COP rms (p<0.0001) and COP velocity (p<0.0001). However, similar to the typically developing children the type of visual scene did not significantly alter the posturographic measures (Figure 3.20b&d). Similarly, segmental movements at the head and trunk did not appear to be significantly affected in children with BVL when comparing the pitch angle rms (Figure 3.21a&b) and roll angle rms (Figure 3.21c&d). Segmental measurements were largely unaffected in typically developing children (Figure 3.22). An interaction was noted between task and environment when looking at segmental roll angle rms values at the head and trunk (task*environment, p=0.005), with slightly greater roll angle measurements being observed in the static visual scene in all of the eyes open tasks except when children stood on one. However, this was more likely related to the significant difference seen based on task difficulty rather than visual scene.

Summary of Aim 2

In the paired tasks of the BOT-2 when tasks were performed both with eyes open and closed, balance improved when eyes were open in both groups of children when compared by time to fall and posturography. The effect of vision on the ability to remain upright longer and maintain postural control was greater for children with BVL compared to their typically developing peers even in difficult tasks (e.g. standing on one foot with eyes closed). The effect of vision on head and trunk movements varied by the difficulty of the task. Reductions in head and trunk movement were seen in the easiest tasks (two feet on a line) when eyes were open and this effect appeared to be greater for children with BVL. Head and trunk pitch angles were reduced when eyes were open in the one-footed task but no interaction with group was seen. The presence of moving cars and pedestrians in the visual scene did not alter BOT-2 scores, time to fall, or postural control for either group of participants. Segmental measures did not differ significantly between conditions for either group.

Figure 3.20. Impact of visual environment on postural control in eyes open tasks. Balance was compared by COP rms (A and B) and COP velocity (C and D) while children performed the 4 eyes open tasks in a static visual environment where objects in the virtual environment were kept still and in a dynamic visual environment where cars and pedestrians moved past the participants. The x-axis lists the eyes open tasks: Task 1: two feet on a line; Task 3: one foot on a line; Task 7: one foot on a balance beam; Task 8, two feet, on a balance beam. Statistical results for a two-way [visual environment (2)]x[task (4)] repeated measures ANOVA are reported below each set of tasks.

Figure 3.21. Impact of visual environment on head and trunk movement in children with BVL who use CI. Balance was compared by head (A) and trunk (B) pitch RMS and as well as head (C) and trunk (D) roll rms while children performed the 4 eyes open tasks in a static visual environment where objects in the virtual environment were kept still and in a dynamic visual environment where cars and pedestrians moved past the participants. The x-axis lists the eyes open tasks: Task 1: two feet on a line; Task 3: one foot on a line; Task 7: one foot on a balance beam; Task 8, two feet, on a balance beam. Statistical results for a two-way [visual environment (2)]x[task (4)] repeated measures ANOVAare reported below each set of tasks.

Figure 3.22. Impact of visual environment on head and trunk movement in typically developing children. Balance was compared by head (A) and trunk (B) pitch RMS and as well as head (C) and trunk (D) roll rms while children performed the 4 eyes open tasks in a static visual environment where objects in the virtual environment were kept still and in a dynamic visual environment where cars and pedestrians moved past the participants. The x-axis lists the eyes open tasks: Task 1: two feet on a line; Task 3: one foot on a line; Task 7: one foot on a balance beam; Task 8, two feet, on a balance beam. Statistical results for a two-way [visual environment (2)]x[task (4)] repeated measures ANOVA are reported below each set of tasks.

3.3 The Impact of Audition on Balance in Children with BVL

Binaural hearing allows for the localization of sound emitting objects in our surrounding environment, contributing to the perception of acoustical flow during movement. This can aid in our spatial understanding of the environment, particular for components of the environment that are outside of our field of view. It is possible, that in the absence of vestibular input, children with BVL may use sound information to aid in their spatial awareness and plan postural control strategies. Children with bilateral cochleovestibular loss, have the ability to hear and localize sounds through bilateral CI. In the following sections we will examine the impact of audition on balance in children with BVL.

3.3.1 Impact of Restoration of Hearing Through Bilateral Cochlear Implantation on Balance

Previous work from our laboratory has suggested a small but significant improvement in static and dynamic balance when CI are turned on (Cushing, Chia, James, Papsin, & Gordon, 2008). In the following section we will further investigate this finding and explore the effects of wearing CI on the components of postural control.

In Figure 3.23, there is a small but significant improvement in balance scores from 4.5 (0.4) with implants on to 5.2 (0.4) (p=0.029) when BOT-2 scores were examined by a paired t-test. Balance abilities improved when implants were on in 50% of children with BVL, with BOT-2 scores improving 1.4 (range 1-3) scaled score points in those who improved (Figure 3.24). Children whose balance improved when CIs were 14.9 years old on average and participants whose balance did not improve were 13.7 years. The age differencedid not reach significance (p=0.21). The duration of implant use for the first CI (11.0 vs 12.1 years, respectively) and the second CI (4.3 and 3.9 years, respectively) Figure 3.23. BOT-2 scaled scored were not significantly different between those improves when implants are turned on.

whose balance did or did not improve. No etiological differences were seen between groups. Two children with unknown etiologies of hearing loss (age 15.9 and 16.5 years) actually saw a decrement in balance function by 1 scaled score point when implants were turned on. When balance in each of the tasks was compared by time to fall (Table 3.4) no differences between implant on and off were observed using a two-way [(implant status (2)]x[task (7)] repeated measures ANOVA.

Postural control measured by COP rms and velocity was compared while children balanced with implants on and off using a two-way [(implant status (2)]x[two-footed task (3)] mixed factorial ANOVA. When two-footed tasks were made more challenging by closing eyes or standing on a balance beam, postural control appeared to improve when children with BVL had their implants turned on, demonstrated by reductions in COP rms in Figure 3.25a. Significant reductions in COP rms were not seen in one-footed tasks when compared by a two way [(implant status (2)]x[one-footed task (4)] repeated measures ANOVA. However, a trend towards significance was seen when children wore their implants while standing on one foot with eyes closed using a paired t–test (p=0.058)(Task 6: one foot on a line, eyes closed). The COP velocity was not significantly different when children with BVL stood in the two-footed stances despite the improvement in COP rms (Figure 3.24c). COP velocities appeared to actually increase in the one-footed stance tasks when implants were on, but this did not to reach statistical significance (Figure 3.25d).

Movement at the head and trunk was then compared while children with BVL balanced with implants on and off using a two-way repeated measures ANOVA as described above. No statistically significant differences in pitch angles measured at the head (Figure 3.26a&b) or trunk (Figure 3.26c&d) were observed in any of the tasks. Head roll angles compared by rms were not different in the simplest two-footed (Figure 3.27a) and one-footed (Figure 3.27b) tasks where eyes were open and the tasks were performed on solid ground. However, when the tasks were made more difficult by either taking away vision (eyes closed, task 4, 6,9) or constraining somatosensory input with a balance beam (task 7,8, 9) head roll measurements appeared to decrease when implants were turned on in both two- and one-footed stance tasks (Figure 3.27a&b), but this did not reach statistical significance. Trunk roll measurements did not reveal a significant change in trunk position between implant conditions in the two-footed stances (Figure

3.27c). Similar to head roll, in the least challenging one-footed task when eyes were open and children stood on solid ground (Task 3, Figure 3.27d) trunk roll deviations did not differ over the course of the trial. However, as sensory inputs became more limited in the one-footed stance tasks, a significant reduction in trunk roll angle rms was observed when children wore their implants and turned them on (p=0.029).

Figure 3.24. Balance improvements with CI on. BOT-2 balance scores with implants on are plotted against BOT-2 scores with implants off using a modified Glasgow Benefit Plot. The diagonal line represents scores that did not change with implant status. The majority of implant wearers improved their balance or stayed the same and only two patients had a deterioration in their balance scores.

Task 1 Task 3 Task 4 Task 6 Task 7 Task 8 Task 9 Implant mean mean mean mean mean mean mean Source F df p status (sd) (sd) (sd) (sd) (sd) (sd) (sd)

8.8 6.9 7.0 2.5 4.7 4.2 1.9 Task 30.9 6,102 <0.001 On (0.5) (0.8) (0.7) (0.4) (0.8) (0.7) (0.3) Implant 0.78 1,17 0.391 8.4 6.7 6.2 2.3 5.4 4.1 1.4 Off Task* (0.7) (0.9) (0.7) (0.4) (0.9) (0.7) (0.2) 0.82 6,102 0.554 implant Table 3.4. Time to fall comparison between implant on and implant off.

Figure 3.25. Impact of auditory input through CI on postural control. A) Postural control is significantly improved as two footed tasks become more difficult when measured by the COP rms. B) A similar trend was not seen in one-footed tasks (* p=0.058). Implant status did not alter the COP velocity for either two-footed (C) or one-footed (D) tasks. Statistical results for a two way [(implant status (2)]x[two-footed task (3)] repeated measures ANOVA or a two way [(implant status (2)]x[one-footed task (4)] repeated measures ANOVA are reported below each set of tasks.

Figure 3.26. Impact of auditory input through CI on head and trunk pitch. Head pitch was not significantly affected by implants status for either two footed or one footed tasks (A and B). Trunk pitch was not significantly affected by implants status for either two footed or one footed tasks (C and D). Statistical results for a two way [(implant status (2)]x[two-footed task (3)] repeated measures ANOVA or a two way [(implant status (2)]x[one-footed task (4)] repeated measures ANOVA are reported below each set of tasks.

Figure 3.27. Impact of auditory input through CI on head and trunk roll. Head roll was not significantly affected by implants status for either two-footed or one-footed tasks (A and B). Trunk roll was not significantly affected by implants status for either two footed (C). A reduction in trunk roll RMS was detected in the one-footed stance tasks (D). Statistical results for a two way [(implant status (2)]x[two-footed task (3)] repeated measures ANOVA or a two way [(implant status (2)]x[one-footed task (4)] repeated measures ANOVA are reported below each set of tasks.

3.3.2 Impact of Directional Sound Cues on Balance in Children

In our previous analysis, there was a suggestion that balance may improve when children with BVL wear bilateral CI. Therefore, we next wished to understand if the type of sound they hear impacts their balance. In their day-to-day environment children are exposed to a dynamic sound environment. Localization of sound emitting objects could theoretically improve balance in children by providing spatial information. Alternatively, moving sounds could conceivably be confusing and turn a routine activity like standing at a street corner into a risky activity. Therefore, in this section we compare balance in children in two sound environments: a dynamic sound environment where sound was congruent with the street scene and a white noise environment where no directional cues were present.

Balance ability measured by the BOT-2 was compared in the two sound environments when compared by a 2 (sound environment) x 2 (group) mixed factorial ANOVA (Figure 3.28). Balance ability as measured by the BOT-2 did not differ between children balancing in a dynamic sound environment or in white noise (p=0.250) and no interaction was seen between environment and group (p=0.157). Individual tasks were then compared using time to fall using a Figure 3.28. Balance measured by the BOT-2 was not between group design two- affected by the presence or absence of directional cues in way [sound environment the sound environment in either normal hearing children or children with BVL who use CI. The dynamic sound (2)]x[task (7)] mixed environment (SE) consisted of moving auditory sounds factorial ANOVA (Figure that were congruent with the visual street scene. The static sound SE consisted of white noise with no directional 3.29). As seen previously, components. The dashed line indicates the population time to fall differed between mean based on normative data. tasks and participant groups, but the type of sound environment did not alter the time to fall significantly for any of the tasks in either group (Table 3.5).

Overall, no significant differences were seen when postural control was compared by COP rms between the dynamic sound and the white noise environment (Table 3.6). Individual task comparisons can be seen Figure 3.30a&b for children with BVL and Figure 3.30c&d for typically developing children. In Figure 3.30b, a large increase in COP rms can been seen in children with BVL when balancing on one foot with eyes closed (Task 6) in the dynamic sound environment compared to the white noise environment. When this was examined individually using a paired t-test, a significant difference was detected (p=0.0018). Postural stability was also assessed using the COP velocity (Figure 3.31). COP velocity, differed significantly between groups but also was significantly greater in the directionless, white noise environment, particularly for the one-footed tasks where a statistically significant interaction was seen between environment and group (Table 3.7). In the two-footed tasks comparisons are reported in table 3.7, showing a significant interaction occurred between task, sound environment and group. In Figure 3.31a, it appears that reducing somatosensory input by having children stand on a balance beam, was related to a significant increase in COP velocity for children with BVL balancing in the white noise environment. A similar increase was not seen in typically developing children balancing on two feet in the absence of spatial auditory cues. COP velocity was similar for the simplest one-footed task (Task 3) between sound environments for both groups. However, as the tasks became more difficult, a trend towards an increase in COP velocity was seen for children with BVL balancing in white noise, but this did not reach statistical significance (p=0.063) (Figure 3.31b). Interestingly, typically developing children showed a similar increase; however, COP velocity increased significantly (p=0.039) in the absence of spatial sound cues (Figure 3.31d). Children who were found to have improved their postural stability were further investigated for differences in their demographic information. Children with BVL with reduced COP velocities in the easiest two-footed task received their first implant earlier in life (2.1±1.2 years of age) than children who did not improve or had increased COP velocities (3.6±2.0 years) in the presence of directional sound cues in the environment, but this did not reach statistical significance (p=0.08). Although the age at which the children who improved in the dynamic sound environment received their second implant was 2 years earlier than their peers who did not improved (9.2±3.9 vs 11.2±4.2, respectively) this difference was not statistically significant (p=0.34). As a group, children who showed improved postural stability on one-footed tasks (task 6 and 7) in the dynamic sound environment were slightly older (15.4±3.0 years) than children

whose COP velocities increased (13.4±3.0 years, p=0.02). When the groups were compared by age individually, this trend was not significant.

Df F Sig. Task 6, 198 31.2 <0.0001 Task*group 6, 198 18.5 <0.0001 Sound environment 1, 33 0.24 0.62 Sound*environment*group 1, 33 0.14 0.71 Task*sound environment 6, 198 1.00 0. 43 Task*sound environment*group 6, 198 0.5 0.81 Table 3.5. Time to fall comparisons between the normal hearing children and children with BVL in two sound environments: congruent street sounds and white noise.

Df F Sig. Task 6, 132 18.28 <0.0001 Task*group 6, 132 5.73 <0.0001 Sound environment 1, 22 0.14 0.71 Sound*environment*group 1, 22 0.15 0.71 Task*sound environment 6, 132 0.98 0. 44 Task*sound environment*group 6, 132 1.25 0.29 Table 3.6 Postural stability compared by COP rms between the normal hearing children and children with BVL in two sound environments: congruent street sounds and white noise.

Figure 3.29. The type of auditory input does not alter time to fall. The dynamic sound environment (SE) consisted of moving auditory sounds that were congruent with the visual street scene. The static sound SE consisted of white noise with no directional components.

Figure 3.30. COP rms is not altered by the presence of absence of auditory cues in the environment for either typically developing children or children with BVL who use CI. COP rms was compared between environments in children with BVL who use CI in two-footed tasks (A) and one-footed tasks (B). In task 6 for children with BVL a significant increase in COP rms was seen in the dynamic SE (*p = 0.0018). COP rms was compared between environments in typically developing children while in two-footed tasks (C) and one-footed tasks (D) and no significant differences were detected.

Figure 3.31. Postural stability measured by COP velocity was improved in the presence of directional cues in both children with BVL and typically developing children. COP velocity was compared between environments in children with BVL who use CI in two-footed tasks (A) and one-footed tasks (B). COP velocity was compared between environments in typically developing children two-footed tasks (C) and one-footed tasks (D). Statistical results for a two way [(sound environment (2)]x[two-footed task (3)] repeated measures ANOVA or two way [(sound environment (2)]x[one-footed task (4)] repeated measures ANOVA are reported below each set of tasks.

Only head movements around the pitch axis were affected significantly by the sound environment and this varied by group (Table 3.8). No significant differences were seen in head pitch angle rms in children with CI when balancing in either sound environment (Figure 3.32a&b). Head pitch angles were similar in the two-footed stance tasks for the typically developing group (Figure 3.32d). However, larger angular deviations in head pitch were seen when typically developing children performed one-footed tasks in the directionless, white noise environment (Figure 3.32d). Head roll angles did not differ significantly in either group based on the presence or absence of directional sound input (Figure 3.33). Trunk pitch angles were not significantly affected by the type of sound environment in children with BVL (Figure 3.34a&b). Similarly, trunk pitch angles rms was not significantly different in typically developing children when comparing between sound inputs (Figure 3.34c&d). In Figure 3.34c, a slight increase in trunk pitch angles were seen when children stood on two feet with eyes open (Task 1) and on two feet with eyes closed (Task 4) in the dynamic sound environment, but this did not reach statistical significance (p=0.07). Trunk roll rms for typically developing children and children with BVL are illustrated in Figure 3.35. Slightly greater trunk roll angles were seen in children with BVL between environmental conditions, but they were not statistically significant (p=0.08) (Figure 3.35a).

Df F Sig. One-footed Tasks 3, 90 4.49 0.006 Task*group 3, 90 2.01 0.12 Sound environment 1, 30 0.31 0.58 Sound*environment*group 1,30 4.75 0.037 Task*sound environment 3, 90 0.96 0.42 Task*sound environment*group 3, 90 0.92 0.43 Table 3.8 Head pitch angle rms comparisons between normal hearing children and children with BVL standing on one foot in two sound environments: congruent street sounds and white noise.

Figure 3.32. Head pitch angle was increased in typically developing children but not in children with BVL in the presence of spatial auditory cues. Head pitch angle was not significantly different between environmental sound conditions for children with BVL when standing one two-feet (A) or one-foot (B). Typically developing children did not differ in head pitch rms based on environmental sound when standing on two feet (C). A significant increase in head pitch rms is seen in normal children when balancing in the presence of moving street sounds. Statistical results for a two way [(sound environment (2)]x[two-footed task (3)] repeated measures ANOVA or two way [(sound environment (2)]x[one-footed task (4)] repeated measures ANOVA are reported below each set of tasks.

Figure 3.33. Head roll angles were not significantly altered by environmental sounds in either group. Head roll rms was compared between environments in children with BVL who use CI in two-footed tasks (A) and one-footed tasks (B). Head roll rms was compared between environments in children with normal hearing two-footed tasks (C) and one-footed tasks (D). Statistical results for a repeated measures ANOVA are reported below each set of tasks.

Figure 3.34. Trunk pitch angles were significantly increased by environmental sounds in typically developing children. Trunk pitch rms was compared between environments in children with BVL who use CI in two-footed tasks (A) and one-footed tasks (B). Trunk pitch rms was compared between environments in typically developing children two-footed tasks (C) and one- footed tasks (D). Statistical results for a two way [(sound environment (2)]x[two-footed task (3)] repeated measures ANOVA or two way [(sound environment (2)]x[one-footed task (4)] repeated measures ANOVA are reported below each set of tasks.

Figure 3.35. Trunk roll angles were significantly increased by environmental sounds in children with BVL standing on two feet. Trunk roll rms was compared between environments in children with BVL who use CI in two-footed tasks (A) and one-footed tasks (B). Trunk roll was compared between environments in typically developing children two-footed tasks (C) and one- footed tasks (D Statistical results for a two way [(sound environment (2)]x[two-footed task (3)] repeated measures ANOVA or two way [(sound environment (2)]x[one-footed task (4)] repeated measures ANOVA are reported below each set of tasks.

Summary of Aim 3

A small but significant improvement in balance was seen in children with BVL who use CI when CIs were on. Postural control improved when children with BVL performed the two-footed tasks with implants on demonstrated by a reduction in the COP rms. A similar improvement was not seen in the one-footed stance. Movements at the head and trunk were reduced when children balanced with implants on in both two-footed and one-footed tasks. The type of sound environment did not appear to alter balance using the BOT-2. However, it does appear that postural control measured by the COP velocity demonstrated some evidence of improvement in the directional sound environment. This varied again by task and group with implant users showing reduced COP velocities in the two-footed stances, specifically when standing with two feet on a balance beam. Typically developing children did not exhibit any differences in the two- footed stances but significant reductions in COP velocity were seen in one-legged stances. There was an apparent reduction in COP velocity for children with BVL performing one-legged stances as well, but this did not reach statistical significance. Measurements of head and trunk movement did not reveal any statistically significant differences between sound environments; however, head and trunk roll angle rms did appear greater in the dynamic sound environment.

Chapter 4

4 Discussion

Upright stance is a balancing act that requires us to understand our place in the environment and to combine with it the internal information regarding the alignment of our body segments. To accomplish this, we have developed a range of sensory systems that can help us acquire information about our sensory environment and our body position. Traditionally, these have included vision, vestibular and somatosensory systems (that include tactile, proprioceptive, and kinesthetic inputs). Unfortunately, it appears that up to 70% of children with congenital sensorineural hearing loss can have some form of vestibular dysfunction and up to 40% of children who use CI having total BVL (Buchman, Joy, Hodges, Telischi, & Balkany, 2004; Cushing, Papsin, Rutka, James, & Gordon, 2008; Selz, Girardi, Konrad, & Hughes, 1996). Congenital BVL has been shown to delay motor milestones in infants and it has been demonstrated that children with BVL have impaired static and dynamic balance (Cushing, Chia, James, Papsin, & Gordon, 2008). However, authors have noted that children do eventually acquire their gross motor milestones and that many children with BVL are able to participate in many childhood activities (Cushing, Chia, James, Papsin, & Gordon, 2008; Kaga, Shinjo, Jin, & Takegoshi, 2008; Livingstone & McPhillips, 2011; Siegel, Marchetti, & Tecklin, 1991; Wiegersma & Van der Velde, 1983). These findings suggest that children with BVL compensate for their vestibular dysfunction using other senses such as vision. Indeed, children with congenital sensorineural hearing loss appear to devote increased cortical processing to vision (Finney, Clementz, Hickok, & Dobkins, 2003; Hatzitaki, Zisi, Kollias, & Kioumourtzoglou, 2002; Parasnis & Samar, 1985). Moreover, previous work has demonstrated that children with BVL have an increased reliance on vision for balance (Cushing, Chia, James, Papsin, & Gordon, 2008). Useful spatial information regarding the external environment can also be gathered from auditory input (Lewald, 2013). While, this would otherwise not be of use to children with congenital sensorineural hearing loss, children who receive bilateral CI have access to sound

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input and may be able to use spatial orientation to sound. We assessed these issues in children with BVL who use bilateral CI by addressing the following questions:

1) Is the BOT-2 a valid and reliable measure of balance? 2) Does visual input play a greater than normal role for children with BVL to balance and will this be affected by the presence of moving objects in the visual environment? 3) A. Are children with known vestibular and hearing dysfunction able to compensate for balance problems using hearing restored through bilateral cochlear implants? B. Will different kinds of sound (directional vs. non-directional) impact balance differently?

4.1 Is the BOT-2 Balance Subtest a Valid and Reliable Measure of Balance in Children?

Previous studies from this laboratory have demonstrated impaired balance in children with BVL who use CI using the BOT-2. The BOT-2 balance test is a well-known and widely accepted tool for assessing balance in children. Previous studies have demonstrated moderate test-retest reliability of the BOT-2 (r=0.65), which are similar to other clinical tests in children such as the M-ABC (R. Bruininks & Bruininks, 2005; Henderson & Sugden, 1992). The ability to convert a child’s score to a scaled score and compare overall static and dynamic balance abilities between children makes the BOT-2 an excellent clinical tool. However, a tradeoff exists in that the global score generated by BOT-2 does not permit comment upon which tasks were most difficult for a given child nor the effort they expended completing the task. In keeping with this, it is possible that it may mask balance deficits in children who are able to struggle through tasks to their completion. As a result, the first aim of this work was to determine if the BOT-2 correlates with objective, quantifiable measures of balance such as posturography using force plates and measurements of angular deviations of the head and trunk and to determine if these methods can be used to accurately differentiate between two groups of children with known vestibular function and dysfunction.

In this study, children performing the BOT-2 balance test were recorded using video cameras from two vantage points to allow measurement at two separate time points by individual

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examiners. The global BOT-2 scores demonstrated substantial inter-rater reliability when compared in this way. However, some degree of variation was seen in the reliability between individual task evaluations where inter-rater reliability was determined by looking at the score given to the best trial for each child. This was selected because the best score (defined by trial length or number of steps) is that which is used to calculate the overall global score. Walking tasks had the best agreement between raters compared to stationary tasks. This may relate to the ease with which the steps can be counted in both groups and faults that would stop a walking trial were typically easier to detect than those in standing trials which could be fairly subtle such as taking the hands off the hips. A difference in the inter-rater reliability was also seen within the standing tasks. The easier standing tasks displayed substantial agreements and were stronger than more difficult one-legged tasks that were only fair to moderate in strength. This was likely influenced by the fact that the majority of children were able to carry out the tasks to their completion were therefore generally easier to measure. Interestingly, although the majority of the difficult tasks showed only fair agreement, the last task of the BOT-2 where children stood on one foot on a balance beam with eyes closed agreement increased slightly to moderate (r=0.52). This was largely the most difficult task of the BOT-2 with generally the least amount of success. Faults here were often fairly dramatic and not a matter of interpretation, which may have allowed for better rater agreement. It is also possible that experience of the examiners could have influenced the scoring. It did not take long to realize that this task (task 9) was very challenging for the children with BVL and a fall was likely to occur. This knowledge may have influenced the examiners whereby they may have been primed for falls in this task and more readily hit the stop button when a fall inevitably occurred. This information is useful for clinicians in that while global BOT-2 scores typically agree between raters, there may be some variability in the more difficult tasks.

Next, assessment of known-group validity was assessed by comparing our clinical measures (the BOT-2 score and time-to-fall) and our quantitative measures (force plate posturography and measurement of angular deviations at the head and trunk using motion capture). Overall the BOT-2 was found to be good at differentiating between groups with known vestibular dysfunction with a large effect size. Similarly, the time to fall was also able to determine significant differences between groups of children with and without BVL on a task-by-task basis for all the tasks but the first task, where children stood with two feet on stable ground with eyes

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open. The majority of children in the BVL group were able to accomplish this task in its entirety and therefore a difference was less obvious. Posturographic measures of the COP were also good at differentiating between participants with and without vestibular loss. The greatest differences were seen in the mid-range tasks again with only moderate effect sizes seen in the simplest and most difficult tasks. This finding bears significance for future studies assessing postural control in children, at least in this population. It is possible that simple tasks such as a tandem stance (Task 1) or the side-by-side stance commonly employed in most posturography studies provides insufficient balance constraints on its own to confidently conclude that balance abilities are equal between children with and without vestibular function (H. Suarez et al., 2007). The COP rms and the COP velocity were able to detect significant differences between groups; however, the 95% confidence ellipse was not able to detect differences in all tasks, particularly as they became more difficult. The 95% confidence ellipse is susceptible to error when the task durations are shorter and therefore the statokinesogram will have fewer data points available to calculate the ellipse dimensions which in turn may falsely increase its area (Rocchi, Sisti, Ditroilo, Calavalle, & Panebianco, 2005). As a result, in the more difficult tasks, we were not able to use the 95% confidence for comparison. The angular measurements with motion capture analysis were less effective at differentiating groups. Angular deviations consistently showed statistically significant differences in the two-footed tasks. However, in the one-footed tasks, fewer differences were seen as the tasks became more difficult. Significant differences were seen at the head and trunk in the simplest of the one-footed tasks, but as the tasks became more difficult significance in angular deviations was first lost at the head and trunk around the pitch axis and in the most difficult task, a difference in angular deviations was lost all together. The exact cause of this pattern is unclear. As motor tasks become more difficult, children will limit the degrees of freedom at joints between body segments e.g. the head and trunk or legs and trunk, to simplify motor strategies needed to deal with that task (Assaiante, Mallau, Viel, Jover, & Schmitz, 2005). As a result this may have occurred in both of our age and gender matched groups as task difficulty progressed, negating differences in angular deviations at the head. As task difficulty increased further and greater angular deviations and falls were seen across both groups this may have resulted in the subsequent loss of significance at the trunk.

The clinical tools were compared to the quantitative measurements used in this study. The overall BOT-2 scores did predict impaired postural control; however, this varied by task and

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group. When children with BVL performed moderately difficult tasks such as standing on one foot, poorer BOT-2 scores were predictive of worse postural control. Interestingly, unpublished work in our lab has recently demonstrated that one-footed balance tasks were the most predictive for determining which patients with BVL needed to undergo formal testing for type 1 Usher Syndrome, a condition defined by SNHL, BVL, and eventual blindness secondary to retinitis pigmentosa (Oyewumi, Wolter, Héon, Papsin, & Cushing, 2014). Six of the 18 participants in our study had Ushers Syndrome as the underlying diagnosis of their cochleovestibular loss. Perhaps the underlying impairments in postural control resulting from their bilateral vestibular loss contribute to the predictive utility of this task shown by Oyewumi et al. (Oyewumi, Wolter, Héon, Papsin, & Cushing, 2014). As the tasks became too difficult for children with BVL, correlations were no longer seen between BOT-2 scores and postural control. Conversely, for typically developing children when the tasks were too easy BOT-2 scores did not predict changes in postural control. However, as tasks became more difficult significant correlations were seen. This suggests that for typically developing children, the BOT-2 score is influenced to a greater extent by the more difficult tasks. The time to fall was also compared to the quantitative measures on a task-by-task basis. A similar trend was seen here with time to fall correlating well with postural control measures but varying by task and group vestibular function status (children with BVL vs. typically developing children). An increased time to fall, that is, an ability to remain upright in a balance task for a longer period of time, was predictive of improved postural control (defined by a reduction in COP velocity and RMS) in the easier tasks of the BOT-2 for children with BVL. However, this finding was lost when the balance activities became too difficult. For typically developing children correlations were not seen until the more difficult tasks of the BOT-2 as the easy and moderately difficult tasks were simply too easy to allow for comparison. However, moderate to high strength correlations between time to fall and postural control were seen in the two most difficult tasks. This knowledge may be of use to clinicians when interpreting BOT-2 scores for children presenting with impaired balance. Easier tasks may be sufficiently predictive for children with SNHL and bilateral vestibular impairment. For typically developing children, impairments in postural control may not be apparent to parents and clinicians in simpler balance tasks. Moreover, parents and children may be advised that although children were able to perform easier tasks at the level of their peers, extra precautions when performing activities that involve more challenging balance activities should be taken to

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avoid injury from falls. The finding that postural control measurements correlated better with clinical measures such as time to fall bears practical use for clinicians as well. Optokinetic systems used here are costly. Given the more consistent ability to detect differences between groups of known vestibular function using posturography compared to angular deviations, it may be more justifiable for clinicians to invest in forceplates rather than optokinetic set ups. However, it is possible that with more sophisticated models of human movements would have been able to detect differences better than our simple measurements and further work is required.

It is possible that with longer durations of time for the easier trials, more correlations would have become apparent in the typically developing group as well (Doyle, Hsiao-Wecksler, Ragan, & Rosengren, 2007). Indeed, many clinical balance measures that depend solely on one task such as the one-leg standing task or the KTK and posturgraphic measures such as the mCTSIB measure balance for 30-60 seconds or longer (L. S. Gabriel & Mu, 2002; Henderson & Sugden, 1992; Schilling & Kiphard, 1974). However, for children several trial lengths of longer duration may be too demanding for their concentration, particularly if they have difficulty communicating or very poor balance (De Kegel et al., 2011). De Kegel et al. demonstrated that trial durations of 10 seconds were sufficient for comparison of balance and had good test-retest reliability (De Kegel et al., 2011). Interestingly, angular deviations of the head and trunk from neutral position did not correlate with our clinical measures. This speaks to our clinical observation that while the BOT-2 may detect impairments in postural control that lead to falls, as this limits the trial length and therefore results in a lower BOT-2 score, but does not comment on how children move while they are performing the task. Human movement is complex often necessitating multi-link computer modeling to approximate it (Koozekanani, Stockwell, McGhee, & Firoozmand, 1980). It is possible that comparison of only two segments as was done in the present study was not sufficiently representative of the complex dynamics of the human body during balance control to detect a correlation (E. Park, Schöner, & Scholz, 2012). De Kegel et al. has proposed that posturography and clinical balance tests provide different, but complementary information (De Kegel et al., 2010). Posturography is a process-oriented tool insofar as it evaluates strategies used for balance control. Clinical balance studies are product-oriented and assess the results of balance control. Motion capture may provide information that bridges these two complementary measures. While our simplified model may not have been predictive of the scores on the BOT-2, understanding how movement of the head and body segments of children with BVL differed

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from their typically developing peers may serve to identity targets for physical therapies in these children. Children with BVL had greater angular deviations at the head and trunk. Improvements in trunk control have been shown to reduce falls in the elderly and in patients following stroke (K. Jung, Kim, Chung, & Hwang, 2014; Verheyden et al., 2004). Physiotherapy strategies that employ exercises that are able to reduce trunk movements may be of use in children with BVL as well. While the head is not thought to contribute significantly to postural instability in adults (E. Park, Schöner, & Scholz, 2012), given the increased head:body ratio in children it is possible that head movement may impact stability to a greater extent in children. The finding that the angular deviations did not correlate with the clinical measures does not preclude their utility as a target to be improved with therapy. Interventions that focus solely on one measure (e.g. a clinical tool or COP results) are less effective at reducing falls than strategies that aim to improve multiple dimensions of postural control (Brown, Whitney, Wrisley, & Furman, 2001; Granacher, Gollhofer, Hortobágyi, Kressig, & Muehlbauer, 2013).

The equivalent balance age of children with BVL was 4.5 years (actual age: 14.3 years) suggesting that these children had, on average, the balance abilities equivalent to a 4.5 year old child. A 4.5 year old child can run but often appears clumsy when trying to perform more complicated tasks like riding a bicycle without training wheels or even standing on one foot. This finding may help explain the dissonance that arises between studies that demonstrate that children with BVL ultimately achieve their major motor milestones and parental reports that while their children are able to participate in many common activities, they often lag behind their peers (Cushing, Chia, James, Papsin, & Gordon, 2008). Children with BVL had impaired postural control when compared to our group of age and gender matched typically developing children and this increased with task difficulty. Although all typically developing children were able to stay upright for the entire duration of the two and one-footed tasks performed on stable ground with eyes open, interestingly, a range of postural control strategies was seen. Several children had COP velocities that were comparable to those seen in the BVL group. Children in the typically developing group were presumed to have normal hearing and vestibular function based on history but no formal testing was performed for this group in the current study. It is possible that they may have had subclinical cochleovestibular deficits that were not detected by the investigators or the children’s parents. That said, these children had normal BOT-2 scores and did not differ from the group in any of the demographic features, save for their age, which

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was significantly younger than the median age of the group. Comparison of movement of the head and trunk demonstrated that children with BVL moved their heads and bodies more while attempting to stay upright. When children stood in tandem stance, a significant difference was seen between groups with smaller head and trunk deviations around the pitch axis. When the stabilizing foot was removed and children stood only on one foot, no difference was detectable between children with and without BVL. The increased head and trunk movements suggest that stability was significantly affected by the challenges of the one-footed stance. However, interestingly it appears that typically developing children were able to reduce pitch deviations by placing the stabilizing foot on the ground in the anteroposterior plane (Tandem stance, figure 3.10 a and b), whereas children with BVL could not. Postural control in the mediolateral plane is not stabilized by the tandem foot stance as the BOS remains narrow in that plane and so not surprisingly, trunk roll angles were larger for both groups and angular deviations increased to a greater extent in children with BVL as the two footed tasks became more difficult. An interesting trend was noted in the one footed stances when looking at head and trunk deviations around the roll axis as seen in Figure 3.11 c & d. Children with BVL had abnormally large angular deviations at the head and trunk. However, while typically developing children started with comparatively low amounts of head and trunk movement, they increased steadily as the task difficult increased meeting those of the children with BVL in the most difficult task (one foot, on a balance beam, with eyes closed). Future physical therapy interventions may be able to use information such as this to develop therapeutic plans to improve balance in children with BVL. Developing the core strength and motor coordination through exercises and games that stabilize trunk movements in the anteroposterior plane while in tandem stance may serve as a suitable starting stating point before attempting more complicated tasks such as standing with one foot on a balance beam which was also difficult for typically developing children. Future studies using electromyography to assess motor function of stabilizing musculature in the lower limbs, trunk and neck would be of use to develop such rehabilitative strategies in this population of children.

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4.2 Does Vision Play a Greater than Normal Role in Balance in Children with Bilateral Cochleovestibular Loss than their Typically developing Peers?

Balance is a multidimensional concept that involves multiple neural systems encompassing both sensory inputs and motor outputs (Shumway-Cook & Woollacott, 2007). The neural components are widely interconnected and our ability to remain upright depends on their seamless interactions. A disruption in any one of these could severely impair balance. As we have seen in the previous section, significant postural control and head and trunk movement differences exists between children with and without vestibular function. Children with BVL also had static and dynamic balance abilities far below those expected for their age. Nevertheless, the fact that they are able to accomplish what they do suggests that they are compensating in some way. We wished to determine if vision played a greater than normal role in balance in children with BVL compared to their peers with normal hearing.

To do this, balance was compared in three sets of tasks that were performed with eyes open and eyes closed: standing on two-feet on stable ground, standing on one foot on stable ground, standing on one foot on a balance beam. Although both groups were able to stay upright longer with eyes open, balance deteriorated significantly more with eyes closed in children with BVL compared to typically developing children demonstrated by a reduction in the time to fall seen in Figure 3.12. Similarly, postural control measured by COP rms and COP velocity was significantly better in both groups when eyes were open, but again, the impact of vision on postural control was significantly greater in our implant users. This confirms a previous finding from our laboratory suggesting that CI users with BVL had an increased reliance on vision for balance (Cushing, Chia, James, Papsin, & Gordon, 2008). Similarly, Suarez et al. demonstrated that postural control improved to near normal in children with BVL when eyes were open on a modified version of the mCTSIB (H. Suarez et al., 2007). This led these authors to conclude that balance impairments resulting from vestibular dysfunction are compensated for by visual and somatosensory inputs and resolved to the level of their typically developing peers. In the present study, when balancing with eyes open in the most simple task (two feet on stable ground) postural control did approach normal. However, when the task difficulty was increased, visual

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input alone was not able to return children with BVL to normal levels of postural control. In the present work, somatosensory/proprioceptive inputs were not disturbed by using a soft, compliant surface as is done in the mCTSIB or modified versions of the SOT. The BOT-2 relies on stance and the balance beam to challenge the somatosensory system (Table 2.3) (R. Bruininks & Bruininks, 2005). As a result, our findings are not directly comparable to studies based on the mCTSIB. However, in the absence of bilateral vestibular input, postural control was not fully re- established by vision or stance alone. This highlights the importance of developing therapeutic strategies to improve balance in this population.

The effect of vision on head and trunk movements was affected by the presence or absence of vestibular function and by the difficulty of the balance task. Reductions in head and trunk movement were seen in the easiest tasks (two feet on a line) when eyes were open and this effect appeared to be greater for children with BVL. This affect was seen primarily for the maximum angular deviations seen during the course of the trial. Relatively little change was seen in the movements of the head and the trunk over the course of the trial except for head and trunk roll when eyes were closed. Both groups saw a significant reduction in head roll rms when eyes were open but this did not vary between groups. However, trunk roll rms did improve to a greater extent in children with BVL when eyes were open reflecting the importance of vision on stabilizing balance when the base of support is narrower in the mediolateral plane. When the difficulty of the balance task was increased by standing on one foot, an increase in head and trunk pitch angles was seen and performance on this condition was significantly improved by the presence of vision in both groups over the course of the trial. An unexpected effect was seen for the variability of the head and trunk measures over the course of the trials in the most difficult balance task-pair where children stood with one foot on a balance beam. Here a reduction in angular deviations measured by the rms was seen when children with BVL closed their eyes. As mentioned previously, this task was simply too hard for these children who often fell immediately upon starting the trial. The reduction in the angular deviations here is likely artifact of an inability to perform this task sufficiently to generate large angular deviations. As such, typically developing children were evaluated individually and a significant increase in the angular deviations at the head and trunk can been seen in figures 3.14 to figure 3.16 when children in this group balanced on one leg on the balance beam with eyes open and closed (panels c and e, respectively). The duration of tasks performed with eyes open was only slightly

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less in typically developing children even when somatosensory input was limited by standing on a balance beam. This is quite impressive, considering the increased variability and speed of the COP adjustments and increased angular deviations at the head and trunk that occurred simultaneously in this task. With vestibular input intact, children were able to tolerate greater amounts of movements to stay upright for longer periods of time even when visual and somatosensory input was limited.

The visual system can provide immediate and precise information about the spatial layout of the immediate environment without significant bodily movement (Waller & Hodgson, 2013). Despite the availability and precision of vision, visual information is often not necessary for performing many simple balance tasks (Waller & Hodgson, 2013). Schwesig et al. reported that congenitally blind patients performed equally well on posturography to sighted individuals in static balance tasks (Schwesig et al., 2011). As alluded to earlier, the perception of our position in space that is necessary for upright stance is a combination of external and internal sensory information. In the study by Schwesig et al., in the absence of vision, participants became adept at utilizing internal sensory information such as vestibular inputs to remain upright (Schwesig et al., 2011). The vestibular system serves to resolve sensory conflict when other sensory inputs are ambiguous or missing altogether, but is also an important contributor to spatial memory, spatial updating, and path integration (Andersson, Hagman, Talianzadeh, Svedberg, & Larsen, 2003; Hufner et al., 2007). These higher order processes are critical for balancing in the absence of external cues. In our study, we saw that in the absence of vision balance was not significantly altered when the vestibular system was intact. Typically developing children were able to remain upright for an equal duration whether eyes were open or closed in the simplest stance. It did appear that vestibular input was important for mediating this effect as balance measured by the time to fall and postural control was worse in children with vestibular loss and this effect became more apparent as the tasks were made more difficult by standing on one foot or the addition of the balance beam. When vestibular input was not present, children with BVL relied more heavily on external cues such as vision for balance than their peers with normal hearing and vestibular function. Clinically, children with BVL and their parents should be encouraged to maintain good eye care with regular yearly, ophthalmological assessment to ensure any changes in vision are detected and optimally corrected. In the home environment, the use of night-lights may help children with BVL navigate safely should they get up at night.

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4.3 Does the Visual Environment Affect Balance in Children?

While typically developing children were able to balance well even when their eyes were closed, it is well accepted that visual environment has powerful effect on posture (Butterworth & Hicks, 1977; Toledo & Barela, 2014; Wade, Lindquist, Taylor, & Treat-Jacobson, 1995). As we move through the environment, the position of the retinal projection of the environment changes generating optic flow that is an important contributor to our sense of position as we navigate through the environment. The pattern of the optic flow informs the CNS of the direction of movement. For example, as an individual turns or moves laterally through space a laminar pattern of optic flow occurs in the opposite direction of the movement (Waller & Hodgson, 2013). If the pattern of optic flow radiates or contracts from a focus of attention this signifies either fore or aft movement of the body or that an object of interest is moving towards an individual or away from them. To determine whether it is the object of interest or the viewer that is moving, this visual information is compared centrally to other sensory inputs such as vestibular information and efference-copy information and an appropriate postural control strategy is used (Shumway-Cook & Woollacott, 2007). Situations exist where optic flow is induced in the absence of physical movement and if this is salient enough the sense of movement still occurs. This phenomenon is known as vection. This illusory movement can be so strong that study participants will make slight postural adjustments opposite to the direction of movement. As we have seen, in moving room studies, infants who are dependent on vision for postural control can even be induced to fall over by large shifts in the environment (Butterworth & Hicks, 1977). Even in static stance, our environments are not still and objects continuously move around us, which could potentially impact balance. Paulus et al. demonstrated increased fore and aft sway as dots projected onto the retina increased and decreased in size (Paulus, Straube, Krafczyk, & Brandt, 1989). As we have seen in the previous section, vision is particularly important for balance in children with BVL. Therefore, we wished to determine the impact of real world visual stimuli on balance in children. To do this, children balanced in two virtual environments: 1) a dynamic environment with cars and pedestrians passing by and 2) a simple static environment where everything was kept still.

Moving objects in the environment did not appear to have an effect on balance in either group when compared by posturography or our clinical measures (the BOT-2 score and time to fall).

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Angular deviations measured at the head and trunk were also unaltered by the presence of passing cars and pedestrians. Given the increased reliance on vision in children, it was hypothesized that BOT-2 scores would decrease and quantitative measure of COP and angular deviations would increase in the dynamic visual environment. Different forms of dynamic visual information can add realism to a virtual environment that includes both global and local elements. Previous work has shown that more global visual motion of the environment that includes peripheral visual can affect self-motion perception by inducing optic flow and this has a significant impact on postural control even in study participants with normal sensory function (Riecke, Väljamäe, & Schulte-Pelkum, 2009). In this study, these powerful peripheral inputs were kept still and instead, local visual cues were provided by the presence of moving objects in the environment. No change was noticed in either typically developing children or in children with BVL. Brain imaging studies in children with congenital and early-acquired SNHL have shown that areas of the auditory cortex are used for processing visual stimuli such as moving visual targets (Finney, Fine, & Dobkins, 2001). Other differences in utilization of visual inputs have been noted in children with SNHL that may be of use in balance. Studies have demonstrated improved peripheral vision in children with SNHL, which is of particular importance in balance and an improved ability to reorient the focus of attention (Bavelier et al., 2001; Dye, Baril, & Bavelier, 2007). It is conceivable that these functions are also dependent on cross-modal cortical reorganization. Some authors have suggested that the extent of this reorganization may limit the benefit of CI in terms of speech and language acquisition (Sandmann et al., 2012). One of the goals of early implantation is to reduce the degree of brainstem and cortical reorganization and maximize CI benefits (K. A. Gordon et al., 2011; Jiwani, Papsin, & Gordon, 2013). If the enhanced abilities to use visual information are underpinned by cortical reorganization, conceivably, early CI implantation could have a negative impact on balance that is dependent on vision particularly in complex visual environments. We did not directly study the effects of these particular visual attributes, which are usually tested in an isolated fashion in laboratory environments. However, when the visual environment was manipulated we did not see a deterioration from the baseline function in children with BVL balancing at a virtual street corner, even when surrounded by moving cars and pedestrians. We did not control for the age and time since first CI and our inclusion criteria only sought out children with a minimum of 8 years CI experience. Therefore, a range of ages at the first surgery

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was seen with a median age of 2.5 years and the second surgery occurring at around 10.3 years. This timeframe would still allow cortical reorganization to occur. Future study would be needed in children implanted early with minimal duration between implants (or bilateral simultaneous implantation) to better understand the effects of CI on these visual parameters. It is also possible that we did not see an effect on balance or postural control as a result of our test set up. In the present study we opted to use a virtual environment with strong depth cues with locally moving objects to create a realistic environment that our participants may encounter in the real world, that is, a busy street corner. Such objects can be attentionally demanding and could conceivably impact balance in this way. It is possible that we did not see a difference in our when participants balanced in the dynamic visual environment compared to static because in the strong visual depth cues to orientation may have been sufficient to overcome the attentional demand of cars and pedestrians passing the children. Perhaps if our dynamic visual environment had used more global visual environment such as those used in the swinging room paradigm or other visual self- motion studies we would have seen a more dramatic effect. Moreover, often studies will select a particular component of vision and study it in isolation or examine the effects of motion in only one plane (e.g. fore and aft). In this study, participants stood at street corner and cars and pedestrians passed in both the mediolateral and anteroposterior directions. It is possible we might have been able to induce postural instability if the moving objects had moved constantly in a single direction creating the type of global optic flow typically associated with self-motion. This may reflect a tradeoff that exists in physiological studies between ecological validity and controlling the environment sufficiently to tease out a desired effect. Finally, while the virtual environment at the CEAL StreetLab is very realistic, recreating the street corner outside of the hospital with high fidelity, it is nevertheless a simulated and safe environment. While we did not set out to assess the impact of factors such as stress, arousal or physical responses to a perceived threat, these can all impact balance. It is possible that in the absence of actual physical danger, children in both groups may have simply ignored the passing cars and pedestrians and this may have contributed to the lack of deterioration in balance. When children are at a real street corner or in the chaotic environment of the schoolyard where passing objects bear the real life consequences of collision, children may not perform as well. In summary, while vision is of greater importance for balance children than their typically developing peers, in this study the

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presence of moving cars and pedestrians in the visual environment did not cause deterioration in balance from baseline.

4.4 Can Balance Be Restored in Children with Bilateral Cochleovestibular Loss Through Bilateral Cochlear Implantation?

Previous work in our laboratory showed a small but significant improvement in balance in children with unilateral CI tested by using the BOT-2 (Cushing, Chia, James, Papsin, & Gordon, 2008). In this work, we wished to further investigate the role of CI in balance in children with bilateral CI and BVL using both our clinical measures: the BOT-2 and time to fall as well as our quantitative measures of postural control and body movement. Again, a small but significant improvement in static and dynamic balance function was seen when implants were on and active in our group children with BVL and bilateral CI. Interestingly, children who showed an improvement in their balance measures were on average 1.2 years older than children who did not improve or stayed the same between conditions, but this did not reach statistical significance possibly due to the small sample size in each group. When the tasks were compared on a task-by- task basis, no difference was seen between the time to fall in each condition. When children were able to stabilize in the anteroposterior direction with a tandem stance, postural control measured by the COP rms was better as the tasks became more challenging by either closing eyes or standing on a balance beam. Standing on one foot with eyes closed (Task 6) was found to be one of the most difficult tasks of the BOT-2, yet children with BVL were able to improve their balance when implants were turned on. Improvements in COP rms were not seen for any of the other one-footed tasks. Angular deviations around the pitch axis were not altered by cochlear implant status at either the head or trunk. However, as seen in Figure 3.26, roll angles at the head and trunk were reduced when implants were turned on as the tasks became more difficult. While the majority of these reductions did not reach statistical significance, the trunk roll angles over the course of the one-footed trials were significantly lower when implants were on and active. Unfortunately, from this study the cause of the slight improvement in static and dynamic balance observed by the improved BOT-2 score when implants were on was not explained by either of our quantitative measures. We did see some improvements in the variability of the COP in the two-footed stances and some a reduction in angular measurements that may have contributed, but further study in this area is required. Interestingly, these improvements were seen when the tasks

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became slightly more difficult by removal or reduction of vision and somatosensory inputs. Given the implications of surgical intervention in the cochlea, vestibular function following surgery has been reported on extensively in the literature and was reviewed in section 1.9. Balance function has also been of interest in this population. Buchman et al. followed patients with unilateral CI using CDP to assess stability (Buchman, Joy, Hodges, Telischi, & Balkany, 2004). They found an improvement in CDP scores compared to preoperative scores and concluded that CI surgery does not have a significant deleterious impact on balance. Conversely, Suarez et al. compared balance in 13 children with unilateral CI, 8 of which had hypoactive vestibular function with implants on and off but did not detect a difference in balance function on mCTSIB (H. Suarez et al., 2007). It is unclear how much vestibular function remained in their patients and saccular function was not assessed. The effects of auditory input may go unnoticed in the presence of residual semicircular canal or otoconial function and this may explain why they did not see a difference. Several studies have demonstrated improved vestibular function following cochlear implantation particularly in balance assessments using CDP when the implant was on and activated in noise (Buchman, Joy, Hodges, Telischi, & Balkany, 2004; Ribári, Küstel, Szirmai, & Répássy, 1999; Szirmai, Ribári, & Répássy, 2001). The mechanism of improved balance function while wearing CI is unclear. As we have discussed, when one sensory input becomes unavailable or unreliable, the balance system will reweight other sensory inputs to resolve these conflicts. Among the non-visual external senses, audition can be used to generate environmental knowledge (Waller & Hodgson, 2013). Audition can be used to detect sound emitting objects in the environment and to detect the scale of the local environment both of which are important in determining our position in the environment (E. B. Goldstein, Yost, Schiffrar, & Humphreys, 2001; Sandvad, 1999). It is possible that when children with bilateral CI and BVL are challenged by constraints on balance as was seen when the two-footed and one- footed stances were made more challenging, bilateral CI users could make use of auditory input to aid in their balance. Alternatively, electrical stimulation of the vestibular nerve could have an effect. Current from the activated cochlear implant is known to spread through the perilymph throughout the cochleovestibular apparatus even to the facial nerve (Bance, O'Driscoll, Giles, & Ramsden, 1998; Cushing, Papsin, & Gordon, 2006). Perhaps, current from the cochlear implants leads to low level of background vestibular activation that is response for the differences

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described in this study and in those seen with CDP (Buchman, Joy, Hodges, Telischi, & Balkany, 2004; Ribári, Küstel, Szirmai, & Répássy, 1999; Szirmai, Ribári, & Répássy, 2001).

4.5 Does the Presence of Directional Sound Cues in the Environment Allow Better Balance than a Directionless Sound Environment?

The auditory environment is an important component of the space in which we live. Humans can localize sound emitting objects with great accuracy and can even use sounds to determine the location of objects in the environment and even the scale of the surrounding space (E. B. Goldstein, Yost, Schiffrar, & Humphreys, 2001; Sandvad, 1999). In one study, participants were played recordings of sounds made in rooms of various sizes and were able accurately determine the approximate size of from a series of pictures (Sandvad, 1999). Although much weaker than other senses, audition can impact postural control. In the absence of other senses, reduced postural sway was observed when stationary sounds were played on either side of both sighted and blind study participants (Easton, Greene, DiZio, & Lackner, 1998). This effect was not as powerful as haptic feedback provided by a cane, yet it suggests that when other senses are missing sound may provide important spatial information. Children with BVL who use CI have access to sound through their implants and as we have shown in the previous section, there was an improvement in static and dynamic balance in children who use CI. With access to bilateral CI, children with BVL could use the ability to localize sound emitting objects in the immediate environment to improve their balance. However, sounds in a child’s environment are rarely stationary. If children with BVL and CI are able to use environmental sounds in their environment, they cannot count on them to remain still. Changes in the position and level of sound can be used to determine the approach of objects. Moving sounds can also have a destabilizing effect on balance. Studies in elderly populations have shown that moving sounds can induce postural sway, especially when vision was limited (T. Tanaka, Kojima, Takeda, Ino, & Ifukube, 2001). In the first part of aim 3 discussed in the previous section we demonstrated that children balancing in a dynamic virtual environment could improve their balance with implants on. In part 2 of aim 3, we wished to determine if the presence of moving sounds in the environment that corresponded to the visual scene (e.g. the sound of a car passing by as the car passed through the visual scene) allowed better balance than a directionless sound environment composed of white noise.

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In this study we did not see a difference in static and dynamic balance measured by the BOT-2 nor was there a significant difference in the time to fall between a dynamic sound environment with moving sounds that were congruent with the visual scene compared to a static sound environment comprised of white noise. Although COP variability was unchanged, evidence of improved postural control was seen by a reduction in COP velocity in the dynamic sound environment compared to the white noise environment. For children with BVL this affect was greatest when standing with two feet on the balance beam with eyes open. No difference was seen when standing on stable ground or when eyes were closed. Postural control in typically developing children standing in the two-footed stances, which typically proved too easy for this group, was not altered by the presence or absences of dynamic sound cues. However, a significant reduction in the COP velocity was seen for the one-footed stances made more difficult by either closing eyes or standing on a balance beam when typically developing children balanced in the dynamic sound environment. While similar reductions were seen in the children with BVL, this did not reach significance. This may be the result of the tasks simply being too difficult for children with BVL. Alternatively, it is possible that with bilateral CI, children with BVL were not able to make use of the dynamic sound cues to the same degree as their typically developing peers with binaural hearing. Children with bilateral CI are able to localize sounds in the horizontal plane (Litovsky et al., 2004; Salloum et al., 2010; Van Deun et al., 2010). However, while bilateral CI users are able to grossly determine if sounds are coming from their right or left, it is possible that small or gradual changes in a sound’s position, such as a passing car, may not provide sufficient contrast between ears to be used appreciably for sound localization. Our children with BVL group used omnidirectional microphone settings which might make their ability to localize sounds even worse relating to front-back confusion and difficulty in determining sound source elevation. The use of directional microphone settings in the future may allow implant users to better detect the stationary sounds sources by moving their head relative to the sound source. The age at which bilateral CI users receive their implants is important in their ability to localize sounds (Steffens et al., 2008; Van Deun et al., 2010). Van Deun et al. determined that children who received their first implant before the age of 2 years and their second implant by the age of 6.5 years performed better on their sound localization task (Van Deun et al., 2010). Our implant users were slightly older when they received both their first and second implants and this may have contributed to the inconsistent improvements seen in

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both our examinations of balance with implants on and off as well as the dynamic vs static sound environments. Of note, in our study there was a trend towards younger age of implantation in those children who improved their postural control demonstrated by a reduced COP velocity in the dynamic sound environment. Gross positional changes of the sound (the car to their left and a moment later to their right) may be sufficient to aid balance in simple tasks and could have contributed to the improvements we did observe.

Although sound is an important method of gaining spatial information about our environment, it is significantly less powerful than proprioception and vision (Welch & Warren, 1980). In studies looking at vection, sound was able to strengthen the illusory sense of movement and could induce vection on its own but was easily overpowered by presenting a stable visual environment (Lackner, 1977; Riecke, Väljamäe, & Schulte-Pelkum, 2009). In our study, the first stance (two feet on a line, eyes open) was likely not challenging enough to require recruitment of additional sensory input. The second two-footed stance was more challenging but lacked visual context for the sound, whereas in the balance beam stance, balance was sufficiently challenged but visual context for the moving sound was available to make use of the sound information for postural control. It is unclear why a similar pattern was not seen for the one legged stances, but perhaps the one legged stance was so challenging that any additional spatial information was helpful. These stances also tended to occur later (task 6,7 and 9) and while conditions were randomized the tasks were offered in the standard order dictated in the BOT-2 manual. By the time these later tasks were reached children may have experienced enough of the visual scene to give context the sounds even when eyes were closed. Attempts to mitigate effects related to fatigue or carry-over were made by randomizing the order of the environmental conditions and providing ample break time between conditions. No significant differences were observed when head and trunk movements were compared between sound environments. Easton et al. examined the role of stationary sounds in postural control and noted a reduction in sway but not in head movement in blind and sighted individuals (Easton, Greene, DiZio, & Lackner, 1998). Similarly, although they were not significant in this study, greater movements mediolateral plane were seen at the head and trunk demonstrated by increased angular deviations around the roll axis for children with BVL in the dynamic sound environment. While Easton et al. used stationary sounds, it has been shown that visually impaired children are better at localizing moving sounds (Lewald, 2013). It has been postulated that this is related to use of active head and body movements to

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create self-induced auditory flow out of surrounding sound sources which is coupled with efference-copy and proprioceptive information from the neck and trunk musculature. In this way they are able to couple the auditory flow with efference-copy, proprioceptive input from the head and trunk to create a more meaningful representation of their environment. It is felt that this likely occurs in sighted individuals as well, but in the presence of more powerful information such as vision or vestibular input it is less important. The moving sound in our study may have made use of similar pre-established pathways. The lack of significant improvement in children may reflect the period of auditory deprivation that occurred prior to CI when the process of coupling these senses begins (Muir & Field, 1979). However, similar to our visual scenarios we chose to assess balance in realistic sound environments where sound moved with the passing cars both in the anteroposterioer direction and mediolaterally. Perhaps, if we had only allowed cars and their accompanying sounds to move in a single plane and in a single direction a predictable pattern of postural adjustments would have been seen.

Although postural control did improve when measured by the COP velocity, the significance of the improvements is unclear in light of the lack of improvement in functional outcomes i.e. time to fall and BOT-2. The results suggest that the type of auditory environment does play some roll in postural control in these children and may reflect another compensatory mechanism used by children to remain upright. However, the effect was not robust enough to improve balance ability to the level seen in typically developing children. These findings may provide insights for future therapeutic strategies, but the fact that neither vision nor audition could establish normal balance in children with BVL highlights the necessity of restoring head referenced positional information in this population.

4.6 Necessity of Restoring Head Referenced Sensory Information in Children with Cochleovestibular Loss

Vestibular dysfunction is common in children with SNHL. We have shown significant impairments in static and dynamic balance as well as impaired postural control in children with SNHL and concomitant BVL. In the elderly, improvements in postural control and a reduction in the number of falls has been demonstrated with multidimensional physiotherapy regimens that focus on balance and core strengthening exercises (Granacher, Gollhofer, Hortobágyi, Kressig,

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& Muehlbauer, 2013). It is possible that children with BVL may benefit from similar activities. Medeiros et al. have studied vestibular rehabilitation therapy children (Medeiros et al., 2005). In their study, they focused on children with acute vestibular losses and their aim was to accelerate vestibular compensation. They used CDP to measure their progress and demonstrated improvements in the components of the SOT that reflect vestibular function. While vestibular compensation is not an option in our study population of children with total bilateral vestibular loss, it is possible that strengthening motor coordination strategies could help in these children. Anecdotally, one of the parents of two children with BVL in our study remarked that their child expressed to her that he had “recently taught himself” that when he was falling to one side he needed to contract with the opposite side to stay upright. Corrective postural movements such as the one described here come naturally to individuals with normal hearing and vestibular function but may not be second nature to children with congenital BVL. As we have seen in our discussion of the dynamic systems model of motor development, these strategies must be learned over time and in the absence of key sensory inputs, may be delayed. However, it should be noted that over 60% of our study participants played team sports (Table 2.1). While the level at which they competed was not evaluated, regardless this would require at least basic motor coordination. Moreover, while the results of Modeiros et al. are encouraging, it is important to note that in elderly patients with BVL, improvements in CDP alone were not correlated in a reduction in falls (Brown, Whitney, Wrisley, & Furman, 2001). Elderly patients who have had a lifetime of normal sensory exposure may find it more difficult to adjust and it is conceivable that increased cortical plasticity in children with BVL would make them more amenable to such regimens. Future studies assessing the role of balance therapy in children with congenital or early acquired BVL are required. Similar findings to those reported by Brown et al. in the pediatric population might suggest that more than simple rehabilitation may be required (Brown, Whitney, Wrisley, & Furman, 2001). Several methods have been proposed to provide additional positional information of the head and trunk including vibrotactile biofeedback mechanisms to galvanic stimulation and vestibular implants (Barros, Bittar, & Danilov, 2010; Della SAntina, Migliaccio, & Patel, 2007; Fridman & Della SAntina, 2012; Golub et al., 2014). The first vestibular implant in humans was recently carried out (Golub et al., 2014). For cochlear implant patients, head referenced sensory input may be re-established through electrical stimulation of the cochleovestibular apparatus (Cushing et al., 2012). Cushing et al. has demonstrated that

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information regarding head position detected by gyroscopes and accelerometers can be transferred electrically via a child’s cochlear implant and this can be used in a meaningful way to improve postural control demonstrated by a modified version of the mCTSIB (Cushing et al., 2012). More recently we have demonstrated improvements in functional balance measurements using this technique to improve BOT-2 scores and increased time to fall in the static tasks of the BOT-2 (Wolter, Gordon, Papsin, & Cushing, 2012). From the preceding sections, it is clear that the absence of vestibular input imposes significant challenges on static and dynamic balance, particularly as balance tasks become more difficult. Therapeutic interventions aimed at filling the sensory gap left by bilateral vestibular loss such as those described here are needed to help these children maximize their potential.

4.7 Future Directions

The findings in the current study prompt a number of intriguing research questions for future work. Further study is required to fully understand the impact of the auditory and visual environmental conditions. For example earlier work in our lab demonstrated an improvement in children with BVL who wore only a single implant. In the current work we have demonstrated a similar improvement in sequentially bilateral implanted children with BVL. Direct comparison of unilateral and bilateral implanted children and sequential and simultaneously bilateral implanted children may help to further elucidate the role of auditory input on balance. Also, in this study we did not assess the role of powerful peripheral visual inputs that tend to have a more salient impact on postural control. Future studies looking at self-motion perception using these strong visual inputs in children with BVL would be of interest to help understand how children with BVL use visual information in postural control. As mentioned, we opted to use Street Lab to test children safely in a realistic environment. To get a better understanding of visual and auditory input future studies may benefit from using more controlled inputs to induce predictable changes. We used a simple two-segment strategy to examine simple angular deviations at the head and trunk. While this served as a starting point, these crude measure may not have been sufficient to fully assess the movements of the participants in our study. Future studies may wish to use an increased number of segments or computer modeling techniques to better approximate human movements. Moreover, in this study we used a number of objective and subjective measures to

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assess the outcomes of balance in the absence of the vestibular system. Future work may benefit from the use of surface electromyography placed over the tibialis anterior and gastrocnemius muscles to get a better understanding of what happens to the support musculature of the lower limbs as children with BVL attempt to balance. Also, in the current work we have demonstrated that static and dynamic balance deficits measured by the BOT-2 and postural control impairments measured by quantitative measures persist in realistic environments. Understanding the functional effects these deficits have on the lives of children is important. We have shown that children with vestibular dysfunction are significantly more likely to experience cochlear implant failure (unpublished data), presumably as a result of head traumas from falls. Future prospective studies that follow children in the implant program and document the history of falls or emergency visits may serve to corroborate this finding and provide an even better understanding of the real-world implications of congenital BVL in this vulnerable population. This study demonstrated that the two-footed tasks were able to consistently detect differences between groups in postural control and body segment movements. These three tasks may lend themselves to development of a short-form balance test that could be used by pediatricians and general practitioners for balance assessment in children suspected of vestibular dysfunction. Animal studies have demonstrated that BVL can result in abnormal spatial memory and path integration (Hufner et al., 2007; P. F. Smith & Zheng, 2013). Studies in adult humans with BVL from bilateral acoustic neuroma or ototoxicity have shown similar results using desktop virtual water-mazes (Brandt et al., 2005). A similar study could be performed in children with congenital and early-acquired BVL to determine if they also demonstrate impairments in spatial memory. If no higher order deficits are seen and children with congenital BVL, this would suggest that children with BVL are able to support spatial memory and path integration sufficiently with their other senses. Such information may help explain the discrepancy seen between balance measures reported in the literature and their functional capabilities in day-to- day life. Moreover, hippocampal volumes on MRI are reduced in patients with acquired BVL and this may contribute to these spatial findings. Children undergoing evaluation or CI receive routine pre-operative MRI and assessments of hippocampal volume at that time in the congenital setting might provide valuable information in this field. Prior to their first CI many children are too young to undergo vestibular-end organ testing easily and therefore diagnosis of BVL is

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necessarily delayed. If children with BVL demonstrate similar reductions in hippocampal volume, routine examination of the hippocampus at the time of their MRI may allow monitoring of children and institution of early conservative balance therapies in children who are suspected of having BVL.

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Chapter 5

5 Conclusions

The BOT-2 is a valid and reliable clinical measure that differentiates well between groups of children with and without vestibular dysfunction. Certain tasks of the BOT-2 correlate well with posturographic differences, but there were differences between groups, where correlations were stronger for the more difficult tasks in typically developing children and for the moderately difficult tasks in children with BVL. Children with BVL were found to have static and dynamic balance abilities far below those expected for their age which may help explain how these children can appear to have normal balance abilities when compared by easier balance tasks, yet are often not able to participate in activities to the level of their peers. Moreover, postural control was significantly impaired in children with BVL and was worse as tasks became more difficult compared to their typically developing peers. Similarly, movements at the head and trunk were significantly greater in implant users, particularly in the mediolateral plane demonstrated by increased roll angles. These findings may provide an important starting point for the development of specific physiotherapy strategies aimed at improving balance in this vulnerable patient population. Children with BVL depended on vision to a greater extent than their peers with normal hearing and vestibular function when measured by time to fall and postural control. This may be of important clinical use when advising parents on safety measures for their children. Activities that involve challenging balance tasks in the dark should be avoided. In the home this may simply mean installing nightlights to prevent falls when children get up at night. We did not see a deterioration in balance when children with BVL balanced in environments where cars and pedestrians passed by compared to a simple, still environment. This may provide clinicians with some comfort regarding how their patients with BVL will fair in real world environments with strong cues to orientation, depth and direction. On the other hand, we also did not see an improvement in balance and therefore the disparity between poor clinical balance test results and

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the abilities of children to carry out their daily activities in the real world cannot be explained by this study alone and further study is required. We found that a proportion of children with BVL improved their balance when their bilateral CIs were on and active. This supports previous work that found a similar finding with unilateral CI. Interestingly, although BOT-2 balance test scores did not change, we saw an improvement in postural control when both children with BVL and typically developing children performed balance tasks where balance was constrained by either visual or somatosensory limitations. The vestibular system has an important role in our percept of the world around us. Otolaryngologists have a unique opportunity to study this fascinating sensory organ in their patient population; however, it is often examined in isolation. To improve the lives of our patients, future examinations must continue to consider the vestibular system in relation to all of the sensory and motor systems involved in posture and movement. It is our hope that this work will serve as a starting point for studies to continue improving our understanding of how children with BVL compensate for their sensory challenges.

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Appendices

Appendix 1 – Individual Vestibular Testing Results for each participant in the children with BVL group

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Appendix 2 – Task 1 multitrait-multimethod matrix for typically developing children

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Appendix 3 – Task 3 multitrait-multimethod matrix for typically developing children

rms 1.00 Trunk roll

angle 1.00 0.53 0.03 angle Trunk (0.1-2.0)

max roll

rms 1.00 0.95 0.97 -0.02 -0.01 pitch pitch Trunk (-0.1-0.1) (-0.3-0.3) angle 1.00 0.92 0.19 0.47 0.02 0.94 angle Trunk <0.0001 (1.1-1.8)

(-0.1-0.3) (-0.4-0.4) max pitch

rms 1.00 0.23 0.40 0.08 0.77 0.81 0.68 Motion Capture Motion

<0.0001 <0.0001 (0.2-0.4) (0.2-0.9) (-0.4-0.8) (-0.8-1.1) Head roll angle

1.00 0.86 0.39 0.14 0.12 0.65 0.94 0.44 0.09 <0.0001 <0.0001 (1.3-2.7) (0.7-1.0) (-0.4-2.3) (-1.7-2.6) (-0.1-1.7) roll angle Head max

rms

1.00 0.19 0.48 0.53 0.03 0.16 0.55 0.25 0.35 0.15 0.58 0.76 pitch pitch Head <0.0001 (0.1-2.1) (0.6-1.9) (-0.3-0.7) (-0.9-1.6) (-1.0-2.8) (-0.3-0.6) angle

1.00 0.96 0.40 0.12 0.69 0.24 0.37 0.25 0.35 0.34 0.20 0.75 pitch pitch angle <0.0001 <0.0001 <0.0001 (1.1-1.6) (0.8-3.3) (0.9-2.6) (-0.2-1.2) (-1.0-2.5) (-1.5-3.9) (-0.2-1.0) Head max

1.00 0.60 0.01 0.44 0.09 0.69 0.65 0.01 0.44 0.08 0.39 0.12 0.63 0.01 0.35 0.16 95 % <0.0001 (0.1-1.0) (0.3-1.3) (0.6-3.0) (0.2-1.1) (-0.1-1.3) (-0.2-2.6) (-0.5-3.9) (-0.3-1.9) Ellipse Ellipse

confidence confidence

1.00 0.78 0.00 0.49 0.05 0.29 0.28 0.84 0.25 0.33 0.05 0.83 0.92 0.50 0.04 time <0.0001 <0.0001 <0.0001 (3.6-9.5) (-2.9-9.2) (7.6-11.4) (7.6-11.4) (6.2-10.2) (0.4-17.7) (-6.5-18.3) (12.1-26.7) (-0.097.8) - (-18.1-22.1) COP over COP

Posturography 1.00 0.12 0.64 0.34 0.19 0.71 0.81 0.05 0.86 0.37 0.15 0.82 0.06 0.83 0.06 0.80 0.74 -0.06 <0.0001 <0.0001 <0.0001 (0.5-1.9) (1.1-2.7) (1.4-4.3) (-0.3-1.5) (-1.1-1.3) (-0.8-4.5) (-3.0-2.4) (-3.9-4.8) (-0.9-0.2) (-0.1-0.1)

COP rms COP fall*

Time to to Time Clinical Test Test Clinical 1.00 0.03 0.91 0.39 0.09 0.62 0.69 0.53 0.86 0.40 0.25 0.44 0.06 0.83 -0.11 -0.11 -0.22 -0.43 -0.13 -0.17 -0.05 -0.22 -0.30 -0.20 score (-0.2-0.3) (-0.7-0.5) (-0.7-0.4) (-0.9-1.0) (-1.3-1.1) (-2.9-0.8) (-0.6-0.3) (-0.5 - 0.3) (-0.5- 0.7) (-1.7- (-0.7-0.06) (-0.07-0.03) Total scaled Total

r r r r r r r r r r r r r sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms rms rms rms

Total Total scaled score to Time fall* COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle Head max roll angle Head roll angle Trunk max angle pitch pitch Trunk angle Trunk max roll angle Trunk roll angle * Time to fall not available for correlation availablefor not fall to *Time

Posturography Capture Motion Clinical Test Test Clinical

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Appendix 4 – Task 4 multitrait-multimethod matrix for typically developing children

rms 1.00 Trunk roll angle 1.00 0.98 angle Trunk <0.0001 (2.4-2.9) max roll 1.00 0.16 0.53 0.19 0.47 pitch pitch Trunk (-0.1-0.1) (-0.2-0.4)

angle rms 1.00 0.60 0.01 0.05 0.83 0.02 0.94 angle Trunk (0.3-1.8) (-1.6-0.2) (-0.5-0.5) max pitch

rms 1.00 0.76 0.04 0.87 0.88 0.87 -0.08 Motion Capture Motion <0.0001 <0.0001

(0.3-0.4) (0.6-1.1) (-0.7-0.5) (-1.0-1.1) Head roll angle 0.11 0.11 1.00 0.95 0.76 0.66 0.93 0.95

-0.08 <0.0001 <0.0001 <0.0001 (2.0-2.9) (0.7-1.1) (2.0-2.9) (-1.8-1.4) (-2.1-3.3) roll angle Head max

1.00 0.43 0.09 0.41 0.10 0.08 0.77 0.30 0.25 0.27 0.29 0.32 0.20 (-0.1-1.2) (-0.7-0.9) (-0.6-2.0) (-0.1-0.4) (-0.2-1.1) (-0.03-0.5) angle rms Head pitch Headpitch

0.11 0.11 1.00 0.93 0.58 0.01 0.57 0.02 0.69 0.22 0.40 0.43 0.08 0.48 0.05 Head angle <0.0001 (1.2-1.8) (0.1-0.8) (0.2-2.1) (-1.0-1.5) (-1.3-3.0) (-0.04-0.7) (-0.02-1.9) max pitch

1.00 0.23 0.08 0.06 0.81 0.09 0.72 0.25 0.34 0.00 1.00 0.35 0.16 0.24 0.36 -0.31 -0.43 95 % Ellipse Ellipse (-2.5-0.6) (-4.5-0.3) (-1.2-1.5) (-2.9-4.0) (-2.0-5.5) (-6.5-6.6) (-0.4-2.0) (-1.8-4.7) confidence 1.00 0.28 0.28 0.26 0.31 0.03 0.92 0.52 0.03 0.50 0.04 0.08 0.77 0.49 0.51 0.04 0.54 0.03 -0.18 time (0.3-9.3) (-3.4-9.9) (-0.6-9.8) (0.7-25.5) (1.8-25.3) (-1.04-3.3) COP over COP (-10.5-11.6) (-10.5-11.6) (-13.7-18.2) (-35.5-17.7) Posturography Posturography 1.00 0.09 0.72 0.72 0.86 0.53 0.16 0.54 0.16 0.55 0.50 0.04 0.21 0.42 0.38 0.13 0.26 0.31 -0.05 -0.17 <0.0001 (0.3-1.0) (-0.1-0.1) (-1.7-1.4) (-3.3-1.7) (-0.9-1.6) (-2.3-4.2) (-3.7-8.4) (-0.3-2.0) (0.2 - 6.5) (0.2- (-1.6 - 4.6) (-1.6- COP rms COP

fall* Time to to Time

1.00 0.42 0.10 0.47 0.17 0.50 0.20 0.15 0.84 0.67 0.28 0.27 0.36 0.15 0.91 0.77 Clinical Test Test Clinical -0.11 -0.11 -0.19 -0.33 -0.36 -0.05 -0.03 -0.08 Total Total score scaled (-0.2-0.3) (-1.2-0.3) (-1.9-0.3) (-0.7-0.5) (-1.9-1.2) (-0.8-2.6) (-0.8-4.7) (-0.6-0.5) (-1.7-1.3) (0.04-0.4) (-0.8-0.04)

r r r r r r r r r r r r r sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms rms rms rms

scaled Total score fall to Time COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle Head max roll angle Head roll angle Trunk max angle pitch pitch Trunk angle Trunk max roll angle Trunk roll angle Clinical Test Test Clinical Posturography Capture Motion

137

Appendix 5 – Task 6 multitrait-multimethod matrix for typically developing children

rms 17 1.00 Trunk roll angle 17 1.00 0.95 <0.0001 (2.0-2.9) roll angle Trunk max

rms 17 1.00 0.39 0.12 0.51 0.04 pitch pitch Trunk (0.03-0.7) (-0.03-0.3) angle 17 1.00 0.87 0.36 0.16 0.42 0.10 angle Trunk <0.0001 (2.3-4.3)

(-0.2-0.9) (-0.2-2.5) max pitch 17 1.00 0.65 0.01 0.78 0.53 0.03 0.64 0.01 rms angle Motion Capture Motion <0.0001 (0.1-0.5) (0.8-2.1) (0.3-1.5) (0.04-0.5) Head roll 17 1.00 0.90 0.68 0.68 0.74 0.76 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 (1.3-2.2) (0.3-1.0) (1.0-3.9) (0.4-1.1) (1.1-3.0) roll angle Head max

rms 17

1.00 0.81 0.84 0.56 0.02 0.67 0.42 0.09 0.43 0.08 pitch pitch Head <0.0001 <0.0001 <0.0001 (0.4-1.0) (0.1-0.9) (0.8-3.5) (0.9-2..0) (-0.1-0.8) (-0.2-2.2) angle

17 1.00 0.96 0.79 0.78 0.56 0.02 0.68 0.52 0.03 0.50 0.04 <0.0001 <0.0001 <0.0001 <0.0001 (1.4-1.9) (0.7-1.8) (1.3-3.4) (0.2-1.5) (1.5-6.1) (0.1-1.6) (0.1-4.1) Head max pitch angle angle pitch

17 1.00 0.78 0.65 0.69 0.67 0.52 0.03 0.63 0.01 0.62 0.01 0.57 0.02 95 % Ellipse Ellipse <0.0001 <0.0001 <0.0001 <0.0001 (1.7-4.5) (1.6-7.5) (1.8-6.9) (0.3-5.9) (1.2-6.7) (3.1-13.o) (4.7-23.9) (2.0-17.1) confidence 17 1.00 0.73 0.78 0.80 0.87 0.80 0.45 0.07 0.56 0.02 0.69 0.63 0.01 time <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 (0.4-1.4) (2.2-5.6) (4.0-9.8) (4.7-8.9) (2.2-8.6) (-0.3-7.0) (6.9-16.8) (2.9-28.4) (4.3-21.9) COP over COP

Posturography 17 0.11 0.11 1.00 0.45 0.07 0.85 0.57 0.02 0.39 0.12 0.41 0.10 0.40 0.32 0.21 0.43 0.09 0.48 0.05 0.47 0.06 <0.0001 (0.2-0.3) (0.1-1.2) (-0.2-1.8) (-0.2-1.6) (-0.5-5.9) (-0.1-4.5) (0.02-1.7) (-0.1-0.2) (-0.4-3.1) (-0.3-1.4) rms COP 17 fall fall 1.00 0.08 0.03 0.01 0.06 0.06 -0.44 -0.88 -0.76 -0.85 -0.89 -0.87 -0.90 -0.52 -0.63 -0.46 -0.46 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 Time to to Time (-0.1-0.01) (-0.5-0.02) (-0.3--0.1) (-0.2--0.1) (-0.4--0.3) (-0.2--0.1) (-0.8--0.1) (-0.2 - 0.01)(-0.2- (-0.1--0.07) (-0.03--0.02) (-0.04--0.01) Clinical Test Test Clinical 17 1.00 0.09 0.73 0.26 0.31 0.82 0.08 0.76 0.60 0.65 0.00 0.99 0.06 0.83 0.08 0.76 0.01 0.97 0.94 0.05 0.86 -0.06 -0.14 -0.12 -0.02

Total score scaled (-0.3-0.3 (-1.1-1.5) (-0.1-0.2) (-0.2-0.1) (-0.3-0.2) (-0.4-0.5) (-0.2-0.3) (-0.9-0.9) (-0.3-0.2) (-0.6-0.7) (-0.4-0.03) (-0.3-0.05)

r r r r r r r r r r r r r sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms rms rms rms

Total Total scaled score fall to Time COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle Head max roll angle Head roll angle Trunk max angle pitch pitch Trunk angle Trunk max roll angle Trunk roll angle * Time to fallto notavailable correlationfor Time *

Posturography Capture Motion

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Appendix 6 – Task 7 multitrait-multimethod matrix for typically developing children

rms 1.00 Trunk roll angle

1.00 0.68 angle Trunk <0.0001 (0.8-3.1) max roll

rms 1.00 0.48 0.05 0.46 0.06 pitch pitch Trunk (0.01-0.1) (-0.01-0.4) angle

1.00 0.91 0.58 0.02 0.43 0.09 pitch pitch angle <0.0001 (2.6-4.3) (0.1-0.6) (-0.1-1.5) Trunk max

rms 1.00 0.67 0.79 0.60 0.01 0.63 0.01 Motion Capture Motion <0.0001 <0.0001 (0.2-0.7) (1.1-2.7) (0.1-0.4) (0.2-1.1) Head roll angle 1.00 0.88 0.82 0.80 0.86 0.63 0.01 <0.0001 <0.0001 <0.0001 <0.0001 (1.5-2.7) (0.8-1.7) (2.6-6.4) (0.5-0.9) (0.5-2.5)

roll angle Head max

rms

1.00 0.56 0.02 0.67 0.56 0.02 0.67 0.34 0.18 0.25 0.34 <0.0001 <0.0001 (0.4-1.8) (0.1-1.1) (1.0-4.3) (-0.5-1.3) (0.07-0.7) (-0.1-0.5) angle Head pitch Headpitch

1.00 0.95 0.70 0.68 0.70 0.72 0.50 0.04 0.29 0.26 pitch pitch angle <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 (1.4-2.0) (0.4-1.4) (0.9-3.3) (0.6-2.1) (2.5-8.0) (-0.7-2.5) (0.03-1.0) Head max

1.00 0.62 0.01 0.48 0.05 0.77 0.63 0.01 0.98 0.88 0.53 0.03 0.45 0.07 95 % Ellipse Ellipse <0.0001 <0.0001 <0.0001 (0.8-4.6) (2.4-6.3) (7.3-9.0) (0.3-4.6) (0.02-7.7) (2.6-14.0) (-0.5-12.6) (19.2-36.1) confidence confidence

1.00 0.65 0.82 0.82 0.85 0.91 0.73 0.86 0.62 0.01 0.48 0.05 time <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 (0.3-1.3) (2.6-5.8) (3.7-7.5) (1.0-5.7) (4.7-10.6) (3.4-10.7) (10.4-17.7) (21.1-42.2) (0.04-15.1) COP over COP

Posturography rms 1.00 0.53 0.03 0.93 0.50 0.04 0.34 0.18 0.73 0.56 0.02 0.91 0.79 0.56 0.02 0.56 0.02 <0.0001 <0.0001 <0.0001 <0.0001 (0.2-0.3) (0.1-1.7) (1.5-2.6) (3.9-9.8) (0.1-1.3) (0.4-3.8) (-0.4-1.9) (0.01-0.2) (0.3-0.37) (0.04-1.2) COP fall*

to Time Clinical Test Test Clinical 1.00 0.02 0.28 0.05 0.04 0.20 0.06 0.15 0.05 0.26 0.14 0.21 -0.56 -0.28 -0.48 -0.50 -0.33 -0.47 -0.36 -0.49 -0.29 -0.37 -0.32 Total Total score scaled

(-0.4-0.1) (-0.7-0.1) (-1.5-0.4) (-0.7-0.2) (-0.2-0.04) (-0.2--0.2) (-0.04-0.01) (-0.1-0.001) (-0.3-0.007) (-0.3--0.01) (-0.5--0.01)

r r r r r r r r r r r r r

sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms rms rms

Total scaled Total score fall* to Time COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle Head max roll angle Head roll angle rms Trunk max angle pitch pitch Trunk angle Trunk max roll angle Trunk roll angle

Posturography Posturography Capture Motion

Test Clinical

139

Appendix 7 – Task 8 multitrait-multimethod matrix for typically developing children

rms 1.00 Trunk roll angle 1.00 0.75 angle Trunk <0.0001 (1.2-3.6) max roll 1.00 0.32 0.21 0.52 0.03 pitch pitch Trunk (0.03-0.5) (-0.03-0.13) angle rms 1.00 0.71 0.55 0.02 0.65 0.01 angle Trunk <0.0001 (0.9-2.9) (0.3-1.4) (0.03-0.4)

max pitch

rms 1.00 0.27 0.30 0.45 0.07 0.44 0.08 0.78 <0.0001 (0.5-1.4) Motion Capture Motion (-0.3-0.8) (-0.1-2.4) (-0.02-0.4)

Head roll angle 1.00 0.85 0.47 0.05 0.45 0.07 0.79 0.82 1.5-3.4) <0.0001 <0.0001 <0.0001 (1.3-2.7) (0.4-1.0)

(-0.2-5.7) (-0.02-2.2) roll angle Head max 0.11 0.11 1.00 0.51 0.03 0.69 0.40 0.41 0.10 0.18 0.50 0.61 0.01 pitch pitch Head <0.0001 (0.7-2.5) (0.5-3.0) (-0.2-2.0) (-0.6-5.4) (-0.3-0.6) (0.4-0.97) angle rms

1.00 0.94 0.58 0.01 0.67 0.56 0.02 0.46 0.07 0.25 0.34 0.62 0.01 <0.0001 <0.0001 (1.7-2.5) (0.3-2.2) (1.3-5.5) (0.5-5.0) (1.2-6.7) (-0.6-1.5) (-0.412.3) Head max pitch angle angle pitch

1.00 0.04 0.87 0.04 0.88 0.68 0.29 0.26 0.34 0.18 0.23 0.37 0.87 0.51 0.04 95 % Ellipse Ellipse <0.0001 <0.0001 (1.4-5.4) (2.7-5.2) (-1.2-1.4) (-2.6-2.9) (-2.8-9.6) (-1.9-9.9) (0.6-14.5) (-9.1-23.2) confidence 1.00 0.94 0.14 0.58 0.08 0.75 0.75 0.36 0.16 0.48 0.05 0.20 0.44 0.95 0.66 time <0.0001 <0.0001 <0.0001 <0.0001 (1.8-2.7) (2.2-3.8) (-5.7-7.7) (4.6-13.3) (8.9-37.9) (8.5-12.2) (-4.5-24.6) (-0.3-26.4) COP over COP (-24.6-53.7) Posturography Posturography 1.00 0.86 0.93 0.20 0.44 0.22 0.39 0.82 0.56 0.02 0.33 0.19 0.35 0.17 0.82 0.64 0.01 <0.0001 <0.0001 <0.0001 <0.0001 (0.1-0.2) (0.3-0.5) (1.0-2.3) (0.5-4.9) (0.9-2.1) (1.3-6.4) (-0.3-0.7) (-0.7-1.6) (-0.9-4.0) (-2.1-10.8) rms COP fall*

to Time 1.00 0.09 0.37 0.33 0.12 0.03 0.09 0.05 0.51 0.52 0.33 0.16 Clinical Test Test Clinical -0.43 -0.23 -0.25 -0.39 -0.53 -0.42 -0.48 -0.17 -0.17 -0.25 -0.36 score (-0.9-0.5) (-2.6-1.3) (-0.4-0.2) (-1.5-0.3)

(-0.3-0.02) (-0.1-0.03) (-0.2-0.03) (-0.5-0.05) (-0.04-0.02) (-0.6--0.04) (-1.4--0.001) Total scaled Total

r r r r r r r r r r r r r sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms rms

Total scaled Total score fall* to Time rms COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle Head max roll angle Head roll angle Trunk max angle pitch pitch Trunk angle rms Trunk max roll angle Trunk roll angle

* Time to fallto notavailable correlationfor Time *

Posturography' Mo5on'Capture''

Clinical'Test'

140

Appendix 8 – Task 9 multitrait-multimethod matrix for typically developing children

rms 1.00 Trunk roll angle

1.00 0.95 angle Trunk <0.0001 max roll (1.9 - 2.8) (1.9-

rms 1.00 0.64 0.01 0.67 pitch pitch Trunk <0.0001 (0.1 - 0.3) (0.1- 0.6) (0.2- angle 1.00 0.82 0.80 0.86 angle Trunk <0.0001 <0.0001 <0.0001 (1.7 - 3.7) (1.7- 0.9) (0.4- 2.2) (1.1- max pitch

rms 1.00 0.81 0.73 0.85 0.81 Motion Capture Motion <0.0001 <0.0001 <0.0001 <0.0001 (0.2-0.5) (0.5-1.4) (0.2 - 0.4) (0.2- 0.9) (0.4- Head roll

angle 1.00 0.97 0.74 0.73 0.84 0.76 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 (2.6-3.5) (0.5-1.4) (1.5-4.6)

1.1) (0.5- 2.7) (0.9- roll angle Head max 1.00 0.22 0.40 0.23 0.37 0.20 0.43 0.40 0.12 0.22 0.40 0.18 0.48 pitch pitch Head (-0.1-0.3) (-0.3-0.8) (-0.2-1.3) (-0.1 - 0.3) (-0.1- 0.3) (-0.1- 0.6) (-0.3- angle rms

1.00 0.71 0.19 0.46 0.23 0.37 0.28 0.28 0.45 0.07 0.20 0.45 0.20 0.44 pitch pitch angle <0.0001 (1.0-3.4) (-0.4-0.8) (-1.0-2.6) (-0.3-1.1) (-0.2-4.2) (-0.4-0.8) (-0.9-1.9) Head max

1.00 0.25 0.33 0.28 0.28 0.38 0.13 0.49 0.04 0.81 0.64 0.01 0.42 0.09 0.50 0.04 95 % Ellipse Ellipse <0.0001 (2.4-98.0) (-5.4-36.6) (-3.1-37.2) (25.8-59.6) (-10.8-30.1) (-30.0-95.7) (2.1 - 127.8)(2.1- (35.7-180.2) confidence confidence

1.00 0.69 0.42 0.09 0.42 0.09 0.62 0.01 0.73 0.65 0.70 0.44 0.08 0.43 0.08 time <0.0001 <0.0001 <0.0001 <0.0001 (1.7-9.8) (-0.7-8.0) (-0.5-8.6) (0.07-0.2) (2.8-12.8) (-2.1-24.9) (-1.5-21.2) (11.6-42.2) (11.6-42.2) COP over COP (10.433.0)-

Posturography rms 0.11 0.11 1.00 0.77 0.91 0.49 0.05 0.40 0.56 0.02 0.64 0.01 0.84 0.72 0.51 0.04 0.57 0.02 <0.0001 <0.0001 <0.0001 <0.0001 (0.2-0.5) (0.4-3.9) (2.7-5.7) (0.1-3.8) (1.1-9.7) (0.07-0.1) (0.03-3.5) (5.5-17.7) (-1.1-10.2) COP COP 13.2)(2.7- 1.00 0.01 0.06 0.03 0.09 0.28 0.19 0.21 0.04 0.76 0.69 -0.11 -0.11 -0.63 -0.79 -0.47 -0.51 -0.42 -0.28 -0.33 -0.32 -0.50 -0.08 <0.0001 (-0.5-0.1) (-0.1-0.1) (-0.3-0.2) (-0.5-0.05) (-0.2-0.05) (-0.2-0.05) (-0.02--0.01)

(-0.2--0.01) (-0.8--0.02) (-0.01-0.001) (-0.05--0.01) Time to fall fall to Time Clinical Test Test Clinical

1.00 0.69 0.01 0.01 0.49 0.31 0.18 0.20 0.76 0.72 -0.72 -0.62 -0.62 -0.64 -0.68 -0.18 -0.26 -0.34 -0.33 -0.08 -0.09 score <0.0001 <0.0001 <0.0001 <0.0001 (0.4-1.5) (0.2-0.1) (-0.2-0.1) (-0.7-0.2) (-0.9-0.2) (-0.4-0.3) (-0.3--0.1) (-0.9--0.2) (-0.3 - 0.06)(-0.3- (-0.1--0.02) (-0.03--0.01) (-0.01--0.001) Total scaled Total

r r r r r r r r r r r r r sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms rms

Total scaled Total score fall to Time COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle rms Head max roll angle Head roll angle rms Trunk max angle pitch pitch Trunk angle Trunk max roll angle Trunk roll angle

Posturography Posturography Capture Motion Test Clinical

141

Appendix 9 – Task 1 multitrait-multimethod matrix for children with BVL

rms 1.00 Trunk roll angle 1.00 0.91 angle Trunk <0.0001 (1.3-2.2) max roll

rms 1.00 0.26 0.31 0.39 0.13 pitch pitch Trunk (-0.2-0.7) (-0.2-1.5) angle 1.00 0.80 0.51 0.04 0.58 0.01 angle Trunk <0.0001 (0.6-1.4) (0.04-1.0) (0.3-2.02) max pitch

rms 1.00 0.71 0.70 0.60 0.01 0.58 0.02 Motion Capture Motion <0.0001 <0.0001 (0.2-0.8) (0.3-1.0) (0.2-1.5) (0.1-0.82)

Head roll angle 0.11 0.11 1.00 0.74 0.27 0.29 0.69 0.55 0.02 0.46 0.06 <0.0001

(0.9-2.6) (0.2-1.8) (-0.5-1.5) (-0.9-1.4) (-0.8-3.3) roll angle Head max 1.00 0.08 0.77 0.36 0.16 0.30 0.24 0.51 0.04 0.04 0.89 0.06 0.83 pitch pitch Head (0.1-3.0) (-0.7-0.9) (-0.5-2.9) (-0.6-2.1) (-1.3-1.5) (-2.4-3.0) angle rms

1.00 0.89 0.46 0.06 0.55 0.02 0.24 0.35 0.38 0.14 0.29 0.26 0.27 0.30 pitch pitch angle <0.0001 (0.8-1.5) (0.4-4.4) (-0.1-1.8) (-0.5-3.5) (-0.8-2.7) (-1.7-5.2) (-01.0-2.6) Head max

1.00 0.56 0.03 0.34 0.20 0.63 0.01 0.69 0.13 0.64 0.40 0.13 0.21 0.44 0.18 0.51 95 % Ellipse Ellipse <0.0001 (1.4-19.2) (6.5-37.1) (-5.0-21.4) (-9.4-68.0) (22.6-88.9) (-27.1-42.5) (-21.7-47.2) (-46.5-89.4) confidence confidence

1.00 0.86 0.46 0.07 0.37 0.16 0.27 0.30 0.44 0.09 0.71 0.42 0.10 0.77 0.86 -0.10 -0.08 -0.05 time <0.0001 (2.0-4.05) (-3.1-63.5) (-24.5-244.0) COP over COP (-14.1-77.4) (-20.7-269.5) (-33.4-99.8) (-144.5-100.7) (-140.7-105.9) (-262.8-221.9)

Posturography 1.00 0.84 0.91 0.75 0.66 0.01 0.43 0.10 0.57 0.02 0.09 0.73 0.43 0.10 0.03 0.90 0.02 0.94 <0.0001 <0.0001 <0.0001 (0.2-0.3) (1.6-4.9) (1.3-6.3) (-0.7-7.7) (-6.8-9.5) (-7.8-8.7) (1.7-19.6) (0.04-0.8) (-1.6-16.3) COP rms COP (-15.7-16.8) 0.11 0.11 1.00 0.01 0.01 0.01 0.02 0.08 0.01 0.41 0.05 0.17 0.16 -0.61 -0.64 -0.63 -0.55 -0.43 -0.40 -0.62 -0.21 -0.49 -0.35 -0.36 (-0.5-0.2) (-0.6-0.1) (-1.2 - 0.2) (-1.2- (-0.4-0.04) (-1.0--0.2) (-0.3 - 0.02)(-0.3- (-21.6--3.3) (-0.2--0.02) (-0.8 - -0.01)(-0.8- (-0.01--0.002) Time to fall fall to Time (-0.004--0.001) Clinical Test Test Clinical

1.00 0.23 0.38 0.21 0.47 0.19 0.31 0.49 0.13 0.10 0.28 0.31 0.30 0.07 -0.33 -0.19 -0.34 -0.26 -0.18 -0.38 -0.42 -0.28 -0.26 -0.27 -0.45 score (-0.2-0.4) (-0.3-0.1) (-0.4-0.1) (-0.3-0.1) (-0.1-0.03) (-0.1-0.05) (-0.2-0.03) (-0.4-0.04) (-0.7-0.03) (-0.02-0.01) (-0.001-0.001) (-0.005-0.001) Total scaled Total

r r r r r r r r r r r r r sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms rms rms rms

Time to fall fall to Time COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle Head max roll angle Head roll angle Trunk max angle pitch pitch Trunk angle Trunk max roll angle Trunk roll angle

Total scaled Total score

Posturography Capture Motion Test Clinical

142

Appendix 10 – Task 3 multitrait-multimethod matrix for children with BVL

1.00 Trunk roll angle rms

1.00 0.97 angle Trunk <0.0001 (1.6-2.1) max roll

1.00 0.57 0.02 0.66 pitch pitch Trunk <0.0001 (0.1-0.3) (0.02-0.1) angle rms

1.00 0.75 0.57 0.02 0.55 0.02 angle Trunk <0.0001 (0.9-2.7) (0.1-0.7) (0.04-0.4) max pitch

1.00 0.42 0.10 0.46 0.06 0.86 0.91 Motion Capture Motion <0.0001 <0.0001 (0.7-1.2) (-0.1-1.4) (-0.1-3.5) (0.3 - 0.6) (0.3- Head roll angle rms 1.00 0.98 0.38 0.14 0.44 0.08 0.82 0.87 <0.0001 <0.0001 <0.0001 (1.6-2.1) (0.5-1.2) (1.2-2.2) (-0.4-2.6) (-0.4-6.5) roll angle Head max 1.00 0.63 0.01 0.66 0.75 0.38 0.14 0.76 0.69 pitch pitch Head <0.0001 <0.0001 <0.0001 <0.0001 (0.2-0.7) (0.1-0.3) (0.1-0.5) (0.1-0.5) (-0.2-1.4) (0.040.2) - angle rms 1.00 0.72 0.78 0.75 0.35 0.16 0.37 0.15 0.76 0.77 pitch pitch angle <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 (0.9-3.0) (0.3-0.7) (0.4-1.3) (0.3-0.7) (0.5-1.3) (-0.3-1.5) (-0.6-3.8) Head max

1.00 0.44 0.09 0.35 0.18 0.36 0.18 0.38 0.14 0.43 0.10 0.65 0.01 0.36 0.17 0.46 0.07 95 % Ellipse Ellipse (-1.6-8.0) (-1.6-8.2) (-1.1-14.2) (-7.5-35.7) (-2.5-15.5) (-2.3-24.6) (13.6-68.0) (-0.8-16.9) confidence confidence

1.00 0.79 0.22 0.40 0.27 0.32 0.25 0.35 0.29 0.28 0.32 0.23 0.42 0.10 0.25 0.35 0.31 0.25 time <0.0001 (0.4-1.1) (-2.6-6.9) (-2.6-6.8) (-4.7-10.9) (-5.6-21.1) (-5.6-56.0) (-3.9-14.1) COP over COP (-4.2 - 13.5)(-4.2- (-10.8-31.3)

Posturography 1.00 0.86 0.96 0.43 0.09 0.32 0.22 0.43 0.10 0.44 0.09 0.44 0.09 0.70 0.40 0.12 0.52 0.04 <0.0001 <0.0001 <0.0001 (0.2-0.3) (0.1-5.3) (5.6-21.1 (-0.4-4.2) (-0.4-4.9) (-0.3-2.6) (-0.2-2.6) (-0.6-7.5) (-2.7-10.5) COP rms COP

(-16.1--8.4) fall fall 1.00 0.03 0.07 0.18 0.14 0.24 0.08 0.18 0.08 -0.88 -0.77 -0.91 -0.54 -0.44 -0.34 -0.37 -0.30 -0.43 -0.34 -0.44 <0.0001 <0.0001 <0.0001

to Time (-0.3-0.1) (-0.5-0.1) (-1.3-0.1) (-0.8-0.04) (-0.2-0.04) (-0.2-0.04) (-0.4-0.02) (-0.02--0.01) (-0.03--0.02) (-0.1--0.04) (-0.3--0.02)

1 Clinical Test Test Clinical 0.58 0.01 0.05 0.04 0.07 0.19 0.05 0.24 0.22 0.21 0.66 0.43 0.34 -0.49 -0.52 -0.47 -0.33 -0.47 -0.30 -0.32 -0.32 -0.12 -0.20 -0.25 score (0.1-0.5) (-0.4-0.0) (-0.3-0.1) (-0.5-0.3) (-0.2-0.1) (-0.12-0.0) (-0.01-0.0) (-0.1-0.03) (-0.4-0.01) (-0.1-0.02) (-0.1-0.04) (-0.1-0.04) Total scaled Total

r r r r r r r r r r r r r sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms

Total scaled score fall to Time rms COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle rms Head max roll angle Head roll angle Trunk max angle pitch pitch Trunk angle rms Trunk max roll angle Trunk roll angle Clinical Test Test Clinical Posturography Capture Motion

143

Appendix 11 - Task 4 multitrait-multimethod matrix for children with BVL

rms

1.00 Trunk roll angle

1.00 0.93 <0.0001 (1.6-2.6) roll angle Trunk max

1.00 0.79 0.87 rms Trunk <0.0001 <0.0001 (0.1-0.2) (0.3-0.5) pitch angle angle pitch

1.00 0.92 0.61 0.01 0.73 <0.0001 <0.0001 (0.1-0.6) (0.5-1.5) (2.02-3.3) Trunk max pitch angle angle pitch

rms Motion Capture Motion 1.00 0.70 0.73 0.49 0.04 0.67 <0.0001 <0.0001 <0.0001 (0.5-1.6) (1.5-4.6) (0.5-2.1) (0.01-0.9)

Head roll angle

1.00 0.99 0.71 0.75 0.53 0.03 0.68 <0.0001 <0.0001 <0.0001 <0.0001 (2.1-2.4) (1.1-3.6) (0.1-2.0) (1.3-4.9) (3.6-10.6) roll angle Head max

rms

1.00 0.66 0.67 0.53 0.03 0.47 0.06 0.26 0.31 0.39 0.12 pitch pitch Head <0.0001 <0.0001 (0.1-0.3) (0.2-0.7) (0.1-1.0) (-0.2-0.5) (-0.2-1.2) (-0.05-2.7) angle

0.11 0.11 0.11 1.00 0.89 0.40 0.40 0.44 0.07 0.31 0.23 0.14 0.60 0.24 0.36 pitch pitch angle <0.0001 (1.9-3.4) (-0.1-0.8) (-0.2-1.8) (-0.1-2.7) (-1.8-7.0) (-0.7-1.2) (-1.2-3.1) Head max

1.00 0.45 0.08 0.65 0.01 0.80 0.76 0.58 0.02 0.76 0.70 0.69 95 % Ellipse Ellipse <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 (8.1-77.5) (-1.7-24.1) (15.6-80.0) (10.0-25.3) (19.8-57.4) (13.3-50.0) (29.2-118.1) (29.2-118.1) (85.5-255.4) confidence 0.11 0.11 1.00 0.76 0.60 0.01 0.72 0.67 0.65 0.01 0.41 0.50 0.05 0.34 0.20 0.43 0.09 time <0.0001 <0.0001 <0.0001 (0.2-0.7) (2.3-16.9) (3.5-15.5) (6.8-35.1) (-5.2-44.4) (-5.7-65.0) (-0.4-143.4) (15.2-52.7) (-5.9-25.3) COP over COP

Posturography rms 1.00 0.85 0.86 0.41 0.12 0.56 0.03 0.68 0.65 0.01 0.38 0.15 0.53 0.04 0.55 0.03 0.54 0.03 <0.0001 <0.0001 <0.0001 (0.1-0.2) (0.7-9.8) (0.7-3.1) (1.4-7.1) (0.4-5.9) (0.1-0.14) (1.2-29.4) (-1.4-8.6) (0.8-14.0) (-0.4 - 3.0) (-0.4- COP fall fall 1.00 0.01 0.04 0.01 0.06 0.09 0.29 0.20 0.41 0.52 -0.75 -0.83 -0.66 -0.50 -0.59 -0.46 -0.43 -0.27 -0.33 -0.22 -0.17 (-0.01- -0.006) <0.0001 <0.0001 (-0.5-0.3 Time to to Time (-0.4-0.1) (-1.3-0.3) (-0.2-0.1) (-0.3-0.03) (-0.6--0.1) (-0.01-0.002) (-0.2-0.004) (-0.1--0.02) (-0.2--0.01) ) Clinical Test Test Clinical 0.11 0.11 1.00 0.38 0.13 0.16 0.19 0.34 0.40 0.09 0.09 0.05 0.23 0.41 0.34 -0.41 -0.37 -0.35 -0.24 -0.22 -0.43 -0.42 -0.48 -0.30 -0.22 -0.25 Total Total score

scaled (-0.1-0.5) (-0.3-0.1) (-0.8-0.2) (-0.2-0.1) (-0.4-0.1) (-0.1-0.03) (-0.1-0.01) (-0.2-0.02) (-0.004-0.001) (-0.03-0.004) (-0.3--0.001) (-0.006-0.001

r r r r r r r r r r r r r

sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms rms rms rms

Clinical Test Test Clinical Posturography Capture Motion

144

Appendix 12 – Task 6 multitrait-multimethod matrix for children with BVL

rms 1.00 Trunk roll angle

1.00 0.71 <0.0001 (0.9-3.0) roll angle Trunk max

rms 1.00 0.93 0.30 0.24 -0.02 (-0.1-0.1) (-0.1-0.5) angle

pitch Trunk 1.00 0.84 0.28 0.27 0.48 0.05 <0.0001 (1.0-2.1) (-0.1-0.3) (-0.002-1.0) Trunk max pitch angle angle pitch

rms Motion Capture Motion 1.00 0.45 0.08 0.28 0.30 0.39 0.13 0.72 <0.0001 (0.5-1.8) (-0.1-1.4) (-0.7-2.3) (-0.1-0.5) Head roll angle

1.00 0.78 0.37 0.16 0.08 0.76 0.75 0.58 0.02 <0.0001 <0.0001 (0.9-2.5) (0.5-1.4) (0.4-3.6) (-0.5-2.8) (-2.9-3.9) roll angle Head max

rms 0.11 0.11 0.11 1.00 0.01 0.96 0.07 0.79 0.41 0.38 0.14 0.89 0.69 -0.04 pitch pitch Head (-0.2-0.2) (-0.4-0.5) (-0.1-1.1) (-0.3-2.1) (-0.3-0.3) (-0.6-0.9) angle

1.00 0.69 0.33 0.21 0.16 0.56 0.43 0.10 0.14 0.59 0.13 0.64 0.92 -0.03 pitch pitch angle <0.0001 (0.8-3.3) (-0.2-1.0) (-1.0-1.8) (-0.3-3.4) (-0.7-1.0) (-2.4-2.2) (-2.9-4.9) Head max

1.00 0.35 0.22 0.50 0.07 0.80 0.05 0.87 0.39 0.15 0.37 0.17 0.05 0.86 0.29 0.30 -0.07 95 % Ellipse Ellipse (-4.1-16.0) (-2.2-54.3) (-11.9-70.9) (-11.9-70.9) (-13.7-10.8) (-24.5-28.6) (-13.7-16.2) (-19.8-59.5) (-33.8-168.5) confidence 0.11 0.11 0.11 0.11 1.00 0.44 0.30 0.32 0.46 0.18 0.56 0.20 0.52 0.18 0.54 0.05 0.87 0.45 0.44 0.12 time (-0.1-0.8) (-5.2-14.3) (-5.6-46.7) (-3.6-31.8) (-7.5-57.9) (16.4-30.6) (-91.4-106.9) COP over COP (-10.2-17.9) (-27.5-49.9)

Posturography Posturography rms 0.11 0.11 1.00 0.22 0.44 0.74 0.27 0.36 0.24 0.42 0.45 0.59 0.03 0.64 0.01 0.46 0.08 0.31 0.27 0.59 0.02 <0.0001 (0.5-6.6) (-0.1-0.1) (-0.8-2.1) (-2.8-6.2) (-0.3-2.8) (1.9-11.8) (1.9-11.8) (0.05-0.2) (1.1-10.6) (-1.8-25.8) (-01.0-3.1) COP COP fall fall 1.00 0.97 0.31 0.22 0.44 0.12 0.66 0.06 0.83 0.13 0.43 0.02 0.95 0.02 0.94 0.40 0.96 -0.01 -0.29 -0.39 -0.21 -0.22 -0.01 Time to to Time (-0.1-0.2) (-0.2-0.1) (-0.2-0.2) (-0.3-0.3) (-0.2-0.2) (-0.1-0.01) (-0.1-0.04) (-0.01-0.002) (-0.02-0.02) (-0.04-0.06) (-0.002-0.004)

Test Clinical 1.00 0.55 0.02 0.25 0.26 0.00 0.99 0.82 0.59 0.02 0.07 0.14 0.31 0.06 0.13 -0.31 -0.33 -0.06 -0.15 -0.58 -0.46 -0.37 -0.26 -0.47 -0.38 Total Total score scaled (0.1-1.1) (-0.1-0.1) (-0.2-0.1) (-0.2-0.1) (-0.5-0.2) (-0.3-0.04) (-0.3-0.04) (-0.01-0.001) (-0.03-0.01) (-0.1-0.002) (-0.1--0.01) (-0.003-0.003)

r r r r r r r r r r r r r sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms rms rms

Total scaled Total score fall to Time COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle Head max roll angle Head roll angle rms Trunk max angle pitch pitch Trunk angle Trunk max roll angle Trunk roll angle

Posturography Capture Motion Test Clinical

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Appendix 13 – Task 7 multitrait-multimethod matrix for children with BVL

rms 1.00 Trunk roll angle 1.00 0.65 0.01 angle Trunk max roll (0.5 - 2.5) (0.5-

rms 1.00 0.50 0.04 0.56 0.02 pitch pitch Trunk (0.010.3) - (0.060.6) - angle 1.00 0.71 0.64 0.01 0.34 0.18 angle Trunk <0.0001 (1.2-4.0) (0.2-1.0) (-0.4 - 1.9) (-0.4- max pitch

rms 1.00 0.24 0.36 0.17 0.50 0.41 0.10 0.67 <0.0001 (-0.6-1.2) Motion Capture Motion (0.3 - 1.1) (0.3- (-0.1 - 0.4) (-0.1- (-0.04-0.4) Head roll angle 1.00 0.83 0.54 0.03 0.28 0.27 0.64 0.01 0.56 0.02 Head angle <0.0001 (0.2-1.1) (-1.0-3.3) max roll (1.2 - 2.7) (1.2- 2.6) (0.3- (0.081.1) -

rms 1.00 0.35 0.16 0.42 0.09 0.10 0.70 0.27 0.29 0.22 0.39 0.43 0.08 pitch pitch Head

(-0.1-0.7) (-0.8-2.5) (-0.3-0.6) (-0.1 - 1.7) (-0.1- 0.5) (-0.4- (-0.12-1.8) angle

1.00 0.78 0.50 0.04 0.29 0.25 0.34 0.19 0.24 0.35 0.50 0.04 0.43 0.08 <0.0001 (-2.3-6.2) (-0.3-4.6) (1.1 - 2.9) (1.1- (0.05-1.9) (0.05-2.1) (-1.1 - 3.9) (-1.1- 1.9) (-0.4- Head max pitch angle angle pitch

0.11 0.11 1.00 0.29 0.27 0.51 0.04 0.00 0.99 0.68 0.07 0.80 0.20 0.46 0.47 0.91 -0.19 -0.03 95 % Ellipse Ellipse (1.4-76.7) (-7.5-24.7) (-33.1-33.6) (-40.8-51.9) (-47.3-23.1) (-87.9-79.1) (-63.694.9)- (-86.9-182.8) confidence confidence

1.00 0.74 0.28 0.30 0.49 0.05 0.21 0.43 0.46 0.07 0.52 0.67 0.61 0.23 0.40 -0.11 -0.11 -0.17 -0.14 time <0.0001 (0.3-1.0) (-0.8-70.3) (-45.2-106.3) COP over COP (-7.5 - 22.6)(-7.5- (-18.8-41.9) (-6.5-125.3) (-41.0-25.1) (-55.7-29.6) (-152.8-101.6)

Posturography rms 0.11 0.11 1.00 0.78 0.80 0.53 0.04 0.90 0.25 0.36 0.46 0.08 0.71 0.24 0.39 0.15 0.61 0.37 0.18 <0.0001 <0.0001 <0.0001 (0.1-0.2) (0.1-0.2) (0.1-5.8) (-3.0-7.7) (-6.2-8.9) (-4.4-7.2) (-1.5-21.7) (-4.4-21.2) COP COP (11.9-21.3) (11.9-21.3) (-13.1-31.4) fall fall 1.00 0.03 0.01 0.09 0.00 1.00 0.28 0.91 0.15 0.46 0.06 0.12 0.64 0.30 0.24 0.53 -0.55 -0.61 -0.43 -0.28 -0.03 -0.37 -0.17 Time to to Time (-0.1-0.1) (-0.4-0.1) (-0.2-0.2) (-0.7-0.1) (-0.6-0.9) (-0.1-0.3) (-0.6-0.3) (-0.01-0.4)

(-0.01-0.01) (-0.04--0.002) (-0.01--0.001) Clinical Test Test Clinical 1.00 0.87 0.10 0.19 0.51 0.10 0.70 0.62 0.41 0.03 0.29 0.26 0.02 0.95 0.16 0.54 0.42 -0.44 -0.35 -0.18 -0.13 -0.21 -0.52 -0.21 score <0.0001 (0.3-0.6) (-0.2-0.1) (-0.1-0.1) (-0.4-0.4) (-0.1-0.1) (-0.3-0.2) (-0.05-0.2) (-0.02-0.002) (-0.4--0.02) (-0.04-0.06) (-0.003-0.001) (-0.002-0.001) Total scaled Total

r r r r r r r r r r r r r sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms

Total scaled Total score fall to Time rms COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle rms Head max roll angle Head roll angle rms Trunk max angle pitch pitch Trunk angle Trunk max roll angle Trunk roll angle

Posturography Posturography Capture Motion Test Clinical

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Appendix 14 - Task 8 multitrait-multimethod matrix for children with BVL

rms 1.00 Trunk roll angle 1.00 0.93 angle Trunk <0.0001 (1.2-1.9) max roll

rms 1.00 0.69 0.58 0.01 pitch pitch Trunk <0.0001 (0.1-0.3) (0.1-0.4)

angle 1.00 0.75 0.58 0.01 0.37 0.14 angle Trunk <0.0001 (1.2-3.5) (0.1-0.8)

(-0.2-1.2) max pitch

1.00 0.33 0.20 0.68 0.76 0.76 rms Motion Capture Motion angle <0.0001 <0.0001 <0.0001 (0.8-3.3) (0.3-0.9) (0.5-1.5) (-0.2-0.8) Head roll 1.00 0.97 0.35 0.17 0.61 0.01 0.72 0.72 Head angle <0.0001 <0.0001 <0.0001 (1.2-7.0) (1.0-3.2) (-0.4-1.8) max roll (1.9 - 2.4) (1.9- 1.9) (0.6-

1.00 0.39 0.13 0.38 0.13 0.12 0.65 0.26 0.32 0.53 0.03 0.69 <0.0001 (0.5-2.0) (-0.1-0.6) (-1.1-3.3) (-0.6-0.9) (-0.2 - 1.2) (-0.2- (0.061.1) - angle rms Head pitch Headpitch

1.00 0.91 0.51 0.04 0.49 0.05 0.25 0.33 0.33 0.20 0.65 0.79 pitch pitch angle <0.0001 <0.0001 <0.0001 (1.1-1.9) (1.4-3.5) (-0.6-1.7) (-1.3-5.9) (0.4 - 1.9) (0.4- (0.04-1.0) (0.01-2.3) Head max

1.00 0.60 0.01 0.46 0.07 0.81 0.84 0.40 0.12 0.56 0.02 0.88 0.91 95 % Ellipse Ellipse <0.0001 <0.0001 <0.0001 <0.0001 (5.9-43.6) (-3.5-67.1) (20.6-49.6) (46.7-88.6) (50.6-109.8) (84.2-145.6) (26.0-305.5) (-17.2-127.5) confidence 1.00 0.37 0.16 0.38 0.14 0.21 0.44 0.38 0.14 0.36 0.18 0.08 0.76 0.21 0.43 0.13 0.64 0.24 0.37 time (-0.1-0.6) (-3.9-24.9) (-4.2-26.2) COP over COP (-16.2-35.4) (-44.6-59.8) (-22.6-35.4) (-68.0-151.1) (-26.4-67.2) 56.4)- (-11.4 Posturography Posturography 1.00 0.65 0.01 0.87 0.64 0.01 0.47 0.06 0.70 0.76 0.47 0.06 0.65 0.01 0.74 0.80 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 (1.6-5.8) (1.0-5.4) (-0.3-8.2) (0.04-0.2) (4.4-12.9) (7.8-38.5) (3.3-10.4) (6.9-17.4) (-0.6-16.2) COP rms COP (0.07-0.14) 0.11 0.11 1.00 0.07 0.46 0.83 0.67 0.32 0.28 0.01 0.97 0.32 0.07 0.80 0.94 -0.47 -0.76 -0.20 -0.06 -0.25 -0.28 -0.26 -0.02 <0.0001 (-0.1-0.1) (-0.1-0.2) (-0.2-0.1) (-0.4-0.1) (-0.2-0.2) (-1.1-0.4) (-0.2-0.2) (-0.3-0.3) (-0.04-0.002) (-0.004-0.002) Time to fall fall to Time (-0.01--0.003)

Test Clinical 1.00 0.62 0.01 0.07 0.14 0.05 0.79 0.94 0.40 0.21 0.23 0.38 0.71 0.59 0.28 -0.47 -0.39 -0.50 -0.07 -0.02 -0.22 -0.32 -0.10 -0.14 -0.28 score (0.1-0.6) (-0.1-0.1) (-0.2-0.1) (-0.1-0.2) (-0.1-0.1) (-0.2-0.1) (-0.5-0.3) (-0.07-0.1) (-0.8-0.04) (-0.02-0.001) (0.003-0.001) (-0.002-0.0001) Total scaled Total

r r r r r r r r r r r r r sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms rms rms

Total Total scaled score fall to Time COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle Head max roll angle Head roll angle Trunk max angle pitch Trunk angle pitch rms Trunk max roll angle Trunk roll angle

Posturography Posturography Capture Motion Test Clinical

147

Appendix 15 – Task 9 multitrait-multimethod matrix for children with BVL

rms

1.00 Trunk roll angle 1.00 0.89 angle Trunk <0.0001 (0.9-1.7) max roll

1.00 0.08 0.22 -0.44 -0.31 pitch pitch Trunk (-0.8-0.2) (-0.6-0.04) angle rms

1.00 0.95 0.12 0.18 -0.40 -0.34 angle Trunk <0.0001 (-1.2-0.2) (-1.7-0.3) (1.7 - 2.4) (1.7- max pitch

0.11 0.11 1.00 0.29 0.26 0.35 0.17 0.67 0.07 0.79 Motion Capture Motion (-0.2-0.7) (-0.3-1.6) (-0.5-0.8) (-0.8-1.0) Head roll angle rms

1.00 0.93 0.12 0.65 0.15 0.57 0.29 0.27 0.13 0.62 <0.0001 (1.1-1.8) (-0.6-0.9) (-1.1-1.9) (-0.4-1.5) (-1.1-1.8) roll angle Head max 1.00 0.05 0.85 0.09 0.74 0.37 0.14 0.27 0.29 0.97 0.02 0.94 -0.01 pitch pitch Head (-0.4-0.5) (-0.7-0.9) (-0.2-1.0) (-0.7-2.0) (-0.9-0.9) (-1.2-1.3) angle rms 1.00 0.88 0.87 0.78 0.42 0.09 0.31 0.23 0.61 0.59 -0.04 -0.07 -0.13 -0.14 pitch pitch angle <0.0001 (1.3-2.3) (-1.1-0.9) (-1.7-1.4) (-0.2-2.2) (-1.1-4.3) (-2.2-1.4) (-3.3-1.9)

Head max 0.11 0.11 1.00 0.08 0.76 0.70 0.57 0.85 0.91 0.01 0.96 0.26 0.68 -0.11 -0.11 -0.16 -0.05 -0.03 -0.30 95 % Ellipse Ellipse (-26.2-34.9) (-50.2-72.9) (-69.9-39.9) (-95.1-79.8) (-78.3-70.7) (-148.4-43.6) confidence confidence (-173.4-116.1) (-173.4-116.1) (-167.7-176.6)

1.00 0.13 0.63 0.07 0.80 0.78 0.93 0.06 0.83 0.16 0.55 0.30 0.26 0.16 0.24 -0.07 -0.02 -0.37 -0.31 time (-0.8 - 1.2) (-0.8- COP over COP (-47.5-60.7) (-123.4-94.9) (-102.2-94.4) (-92.5-167.7) (-280.9-49.5) (-139.4-169.9) (-132.1-449.4) (-385.9-103.4) Posturography Posturography

rms 1.00 0.33 0.25 0.85 0.06 0.85 0.12 0.67 0.13 0.65 0.32 0.27 0.88 0.05 0.88 0.90 0.16 0.58 -0.04 -0.04 <0.0001 (-5.0-7.6) (-6.0-9.3) (-9.7-8.4) (-0.4 - 0.1) (-0.4- 3.4) (-2.9- (-7.6-24.7) COP COP (0.050.1) - (-11.4-10.1) (-11.4-10.1) (-11.2-19.2) (-22.1-25.5) fall fall 1.00 0.15 0.12 0.38 0.55 0.59 0.98 0.58 0.24 0.20 0.37 0.14 0.24 0.35 -0.41 -0.41 -0.24 -0.16 -0.14 -0.01 -0.15 -0.30 -0.32 Time to to Time (-0.1-0.1) (-0.2-0.1) (-0.2-0.1) (-0.4-0.1) (-0.1-0.4) (-0.14-0.1) (-0.04-0.3) (-0.07-0.04) (-0.001-0.001) (-0.02-0.003) (-0.001-0.0001) Clinical Test Test Clinical 1.00 0.84 0.02 0.95 0.18 0.50 0.01 0.98 0.82 0.81 0.14 0.60 0.33 0.20 0.69 0.75 0.30 0.72 -0.05 -0.06 -0.06 -0.27 -0.09 Total Total score scaled <0.0001 <0.0001 (0.1-0.3) (0.2-0.6) (-0.7-0.6) (-0.1-0.1) (-0.1-0.1) (-0.3-0.1) (-0.3-0.2) (-0.06-0.3) (-0.07-0.06) (-0.001-0.001) (0.0001-0.001) (-0.010.01)-

r r r r r r r r r r r r r

sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. sig. 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI 95% CI

rms rms

Total scaled Total score fall to Time rms COP over COP time 95 % confidence Ellipse Head max angle pitch Headpitch angle rms Head max roll angle Head roll angle Trunk max angle pitch pitch Trunk angle rms Trunk max roll angle Trunk roll angle

Posturography Posturography Capture Motion

Test Clinical

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