Clinical and Spatiotemporal Aspects of Gait: A Secondary Analysis of the Walking Characteristics of Subjects with Sub-acute Incomplete Spinal Cord Injury

by

Kristina Guy

A thesis submitted in conformity with the requirements for the degree of Master of Science Graduate Department of Rehabilitation Sciences University of Toronto

© Copyright by Kristina Guy 2012

Clinical and Spatiotemporal Aspects of Gait: A Secondary Analysis of the Walking Characteristics of Subjects with Sub-acute Incomplete Spinal Cord Injury Kristina Guy Master of Science Graduate Department of Rehabilitation Science University of Toronto 2012

Abstract Objective: To describe the walking characteristics of a sample of ambulatory subjects with sub-acute incomplete spinal cord injury (iSCI). Methods: 52 subjects were included in a secondary analysis of clinical and spatiotemporal measures of walking. The study sample was described as a whole and subsequently divided into subgroups on the basis of 3 clinical factors (etiology, severity, and neurological level of injury) and 4 gait factors (gait aid, velocity, symmetry, and variability). Results: Clinical and spatiotemporal parameters were highly variable across the study population. Sub– groups with unique gait features were best identified by velocity and variability. Conclusions: Spatiotemporal measures of walking provide augmented description of walking in the subacute iSCI population. Sub-grouping by gait factors warrants further investigation with respect to their ability to act as predictors and modifiers of treatment effect.

ii

Acknowledgements Throughout my graduate studies, there have been many people who have contributed to my growth and learning, both personally and professionally. I would first like to thank Professor Molly Verrier for her unwavering support and encouragement as my thesis supervisor. Her passion for the field of neuroscience and particularly for the study of spinal cord injury rehabilitation has been, and continues to be inspiring. I have been so fortunate to have had her guidance and I am truly grateful for the generosity of time she has shown me throughout this long journey. I would also like to thank my committee members who helped to shape this thesis into what it has become. Many thanks to Dr. Bill McIlroy for sharing his knowledge and providing the direction necessary to remain focused. Thank you to Dr. Cathy Craven whose insights led to the initial idea for this study and whose commitment to clinical care helped to ensure that my work had clinical applicability. Thanks also to Dr. Milos Popovic for his encouragement and for including me as a member of his research team. I would also like to thank my dear friend, Dr. Kara Patterson who spent many a late night with me discussing the quandaries of neurology, physiotherapy, education, and health care – the solutions are out there. I am indebted to my colleagues and friends at Toronto Rehab’s Spinal Cord Rehabilitation Program for their immeasurable support and encouragement. In particular, Heather Flett, Helen Morris, Craig Ganley, Gillian Johnston, Carole Chebaro, and Sandra Mills who have each rescued me from the depths of self-doubt and who demonstrate on a daily basis a pursuit for excellence by which I am awe-struck. Finally, I owe my deepest gratitude to my family for being my constant cheerleaders. Thank you to my parents, Ursula and John Guy, for their unconditional confidence in my success, and for showing me what it is to be kind in this world. And to my brother Mike and his wife Melissa, thank you for your love and support – I am grateful for your laughter. I have been fortunate to have worked with many individuals and families who have met the sting of spinal cord injury and I risk doing a disservice by not mentioning them all here. Ultimately it is the sum of my experiences with these individuals that has resulted in a desire to do more, be better, and live fully – there is no adequate way to say thank you for that.

iii

Table of Contents Acknowledgements ....................................................................................................................................... iii List of Tables.................................................................................................................................................. v List of Figures .............................................................................................................................................. vii List of Appendices ....................................................................................................................................... viii Glossary of Terms ......................................................................................................................................... ix 1.0 Overview .......................................................................................................................................1 2.0 Background ..................................................................................................................................1 2.1 Spinal Cord Injury .....................................................................................................................1 2.2 Gait (normal/healthy) ................................................................................................................3 2.2.1 Neural Control of Gait.........................................................................................................3 2.2.2 Normal Gait Cycle ..............................................................................................................4 2.2.3 Spatiotemporal Characteristics of Gait ...............................................................................4 2.2.4 Symmetry of Gait ...............................................................................................................6 2.2.5 Variability of Gait ................................................................................................................6 2.3 Post SCI Gait............................................................................................................................7 2.3.1 Walking Function post-SCI .................................................................................................7 2.3.2 Recovery of Walking post SCI ............................................................................................8 2.3.3 Gait Rehabilitation Approaches Post SCI .........................................................................10 2.3.4 Spatiotemporal Profile of post-iSCI Gait ...........................................................................10 2.3.5 Symmetry of post-iSCI Gait ..............................................................................................11 2.3.6 Variability of post-iSCI Gait ..............................................................................................11 2.3.7 Clinical Measures of Gait in SCI .......................................................................................11 3.0 Objectives ...................................................................................................................................14 4.0 Methods ......................................................................................................................................15 4.1 Participants.............................................................................................................................15 4.2 Measures................................................................................................................................15 4.2.1 Clinical & Functional Measures ........................................................................................15 4.2.2 Spatiotemporal Measures ................................................................................................16 4.3 Data Analysis .........................................................................................................................17 4.4 Results ...................................................................................................................................18 4.4.1 Subjects ...........................................................................................................................18 4.4.2 Clinical Measures .............................................................................................................18 4.4.3 Spatiotemporal Measures ................................................................................................19 4.4.4 Results Based on grouping by Clinical Characteristics ....................................................28 4.4.5 Results Based on Grouping by Gait Characteristics.........................................................32 5.0 Discussion ..................................................................................................................................38 5.1 Total Population .....................................................................................................................38 5.2 Subgroups ..............................................................................................................................43 5.2.1 Clinical Subgroups ...........................................................................................................44 5.2.2 Gait Subgroups ................................................................................................................47 5.3 Limitations ..............................................................................................................................51 6.0 Overall Conclusions ....................................................................................................................53 6.1 Walking in iSCI: Descriptors and Measures ...........................................................................53 6.2 Sub-grouping of subjects with iSCI .........................................................................................54 6.3 Recommendations from current study ....................................................................................54 6.4 Future directions.....................................................................................................................57 7.0 References .................................................................................................................................59 8.0 Appendices .................................................................................................................................69 iv

List of Tables Table 1: Clinical & Functional Measures Abstracted from Subjects' Health Records ............16 Table 2: Spatiotemporal Parameters Obtained for Analysis ..................................................17 Table 3: Summary of Results from Clinical Measures ...........................................................19 Table 4: Summary of Spatiotemporal Results .......................................................................28 Table 5: Summary of Etiology Group Characteristics ............................................................29 Table 6: Summary of LOI Group Characteristics ...................................................................30 Table 7: Summary of SOI Group Characteristics ..................................................................31 Table 8: Summary of Gait Aid Group Characteristics ............................................................32 Table 9: Summary of Velocity Group Characteristics ............................................................35 Table 10: Summary of Temporal Symmetry Group Characteristics .......................................36 Table 11: Summary of Spatial Symmetry Group Characteristics ...........................................36 Table 12: Summary of Temporal Variability Group Characteristics .......................................37 Table 13: Summary of Spatial Variability Group Characteristics ...........................................38 Table 14: Correlations between Spatiotemporal Parameters for Total Study Population ......70 Table 15: Summary of Clinical Measures Results for Etiology Groups..................................73 Table 16: Summary of Spatiotemporal results for Etiology Groups .......................................76 Table 17: Summary of Clinical Measures Results for LOI Groups.........................................78 Table 18: Summary of Spatiotemporal Results for LOI Groups.............................................81 Table 19: Summary of Clinical Measures Results for SOI Groups ........................................83 Table 20: Summary of Spatiotemporal Results for SOI Groups ............................................86 Table 21: Summary of Clinical Measures Results for Gait Aid groups ..................................88 Table 22: Summary of Spatiotemporal Results for Gait Aid groups.......................................91 Table 23: Summary of Clinical Measures results for "No Aid" Group ....................................97 Table 24: Summary of Spatiotemporal Measures Results for "No Aid" Group ......................98 Table 25: Correlations between Spatiotemporal Parameters for the "No Aid" Group ..........101 Table 26: Summary of Clinical Measures Results for Velocity Groups ................................103 Table 27: Summary of Spatiotemporal Results for Velocity Groups ....................................106 Table 28: Summary of Clinical Measures Results for Temporal Symmetry Groups ............109 Table 29: Summary of Spatiotemporal Results for Temporal Symmetry Groups ................111 Table 30: Summary of Clinical Measures Results for Spatial Symmetry Groups ................113 Table 31: Summary of Spatiotemporal Results for Spatial Symmetry Groups.....................116 Table 32: Summary of Clinical Measures Results for Temporal Variability Groups .............118 Table 33: Summary of Spatiotemporal Results for Temporal Variability Groups .................121 v

Table 34: Summary of Clinical Measures Results for Spatial Variability Groups .................124 Table 35: Summary of Spatiotemporal Results for Spatial Variability Groups .....................127

vi

List of Figures Figure 1: Footfall Measurement Conventions ..........................................................................5 Figure 2: Subject Information ................................................................................................15 Figure 3: Velocity Distribution .................................................................................................20 Figure 4: Cadence Distribution ...............................................................................................20 Figure 5: Stance Time Distribution ........................................................................................21 Figure 6: Swing Time Distribution ...........................................................................................22 Figure 7: Single Support Time Distribution ............................................................................23 Figure 8: Double Support Time Distribution ............................................................................23 Figure 9: Temporal Symmetry Distributions ...........................................................................24 Figure 10: Total Temporal Symmetry Distributions.................................................................25 Figure 11: Spatial Symmetry Distribution ..............................................................................25 Figure 12: Temporal Variability Distributions ..........................................................................26 Figure 13: Spatial Variability Distributions .............................................................................27 Figure 14: Model of Walking Measurement Recommendations ............................................56

vii

List of Appendices 8.1

Appendix A: Results for Total Study Population ..........................................................69

8.2

Appendix B: Results for Sub-Groups...........................................................................72

viii

Glossary of Terms Spinal Cord Injury (SCI): damage to the spinal cord resulting in altered sensorimotor control below the neurological level of the lesion Traumatic SCI: an SCI which is caused by a trauma such as a blow, fall, or cut which occurs at a single point in time Non-traumatic SCI: an SCI which is caused by a disease, illness, or degenerative process wherein the symptoms usually develop over time Neurological Level of Injury: “the lowest segment where motor and sensory function is normal on both sides”11 Gait Cycle: the events which occur between two sequential points of initial contact of one lower extremity20, 24 Symmetry: the spatiotemporal similarities between consecutive contralateral steps31; reflects interlimb control32

Variability: the similarities between consecutive ipsilateral steps31; signifies intralimb control32

ix

1.0 Overview The disability resulting from a spinal cord injury (SCI) impacts on nearly every aspect of an individual’s life including activities of daily living (ADLs), mobility, social and mental well-being. Despite the systemic impact of SCI, the restoration of walking function is consistently stated as the highest priority goal among the newly injured1-3. The growing proportion of patients with the potential for the recovery of some degree of walking function4 has contributed to the relative explosion in the study of post-SCI gait and locomotor interventions. The depiction of walking following incomplete SCI (iSCI) is largely dominated by functional description and details of its spatiotemporal features beyond velocity are far less common. It appears that the incorporation of spatiotemporal data might expand the understanding of early post-iSCI gait. The opportunity to characterize the walking patterns of subjects with sub-acute iSCI will contribute to a field currently disproportionately focused on those with chronic injuries. The heterogeneity of the iSCI population results in a high degree of variation in clinical presentation. As a result, patients with iSCI are often categorized according to demographic, etiological, or diagnostic criteria. Arguably, a clear understanding of the variation present in a number of iSCI subpopulations has implications for the future development of targeted walking interventions. However, the degree of variation present in subgroups generated on the basis of gait characteristics has not been extensively reported and this approach may yield important information. The overall aim of the current study is to describe the clinical and spatiotemporal characteristics of a population of patients with sub-acute iSCI. This study will further explore the capacity of a variety of clinical and gait characteristics to identify distinctive groups of iSCI subjects as a preliminary step towards gait impairment classification-directed interventions. 2.0 Background 2.1 Spinal Cord Injury In Canada, the annual incidence of SCI due to trauma is reported to be approximately 35 per million people5 with more recent data from Ontario indicating an annual incidence of 37.2 per million6. Epidemiological information about the incidence of SCI secondary to non-traumatic causes is scarce; however a population-based study in Ontario has shown that 64% of patients receiving inpatient rehabilitation have non-traumatic SCI (NTSCI) 7. Over the last two decades the mean age of an individual with a new SCI has steadily increased to 40.2 years with a growing proportion of patients over the age of 608, 9. In all, there are approximately 85 550 individuals living with SCI in Canada10.

1

2 The consequences of SCI are highly variable due to differing degrees of injury severity and location. The American Spinal Injury Association (ASIA) has published the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) which defines a standard approach to the classification of SCI11. The severity, or completeness, of injury is described using the ASIA Impairment Scale (AIS). The patient is assigned to one of five categories according to the extent of motor and/or sensory preservation present at the time of assessment. The AIS defines the five categories as follows: A – Complete. No motor or sensory function is preserved in the sacral segments S4-S5. B – Incomplete. Sensory but not motor function is preserved below the neurological level and includes the sacral segments S4-S5. C – Incomplete. Motor function is preserved below the neurological level, and more than half of key muscles below the neurological level have a muscle grade less than 3. D – Incomplete. Motor function is preserved below the neurological level, and at least half of key muscles below the neurological level have a muscle grade of 3 or more. E – Normal. Motor and sensory functions are normal11. The neurological level of injury is defined as “the lowest segment where motor and sensory function is normal on both sides”11 (p.2). Individuals whose neurological level of injury is located in the cervical spinal cord (C1 to T1), experience tetraplegia and represent 38.3 and 16.9 percent (incomplete and complete respectively) of the SCI population9. Individuals with paraplegia whose lesions are located in the thoracic, lumbar, or sacral spinal cord (T2 to S5) represent 21.5 and 22.9 percent (incomplete and complete respectively) of the SCI population9. Despite the high level of variability in injury severity, the most consistent consequence of SCI is a significant change in sensorimotor function12. The physical, mental, and social sequellae of SCI are broad and impact nearly every aspect of an individual’s life. As the life expectancy for individuals with SCI continues to increase9, the proportion of life spent coping with disability is also growing12. Although the total population of individuals with SCI is relatively small when compared to those with other neurological conditions (eg. stroke prevalence = 300 000 13 in Canada), the estimated lifetime healthcare and living costs following a SCI have been reported to be as high as 3.3 million US dollars per person depending on the age at injury and injury severity9. The proportion of patients with incomplete SCI (iSCI) has grown to over 50% of new injuries in recent years8, 14, 15. This increase has been attributed to improvements in immediate care following

3 injury, increased safety features in motor vehicles, and a focus on minimizing secondary injury during acute medical care8, 15. Although the outcome for patients with complete lesions is more predictable15, the nature of an iSCI means that these individuals have significant potential for neuroplastic change and functional recovery4. Despite the diverse presentation of impairments among those with iSCI, the restoration of walking function is consistently stated as the highest priority goal1-3. The strong emphasis on the achievement of walking following SCI by both consumers and professionals has undoubtedly contributed to it becoming a key area of focus in both rehabilitation and research in the last 20 years. 2.2 Gait (normal/healthy) Bipedal locomotion has been described as the activity that makes us uniquely human 16 and is frequently deemed a necessary skill for the achievement of daily activities17, 18. Normal gait is characterized by a cyclical pattern of active and passive movements which result from the complex modulation of converging and diverging motor and sensory information16, 19, 20. Ultimately the successful performance of gait requires the precise achievement of progression, stability, and economy19, 20. 2.2.1 Neural Control of Gait The generation of gait requires that the nervous system address two fundamental challenges: the generation of rhythmic motor patterns and the modification of these patterns based on sensory information21. Animal studies have lead to a greater understanding of the neural mechanisms underlying the control of gait22. In lower mammals (such as cats), neuroscientists have discovered that neuronal networks, known as central pattern generators (CPG’s), located within the spinal cord are capable of generating rhythmic movements in the absence of peripheral sensory information21. The details of CPG circuitry in the human nervous system remain largely unknown23. For normal gait to exist CPG’s must be modulated by both sensory and supraspinal input21. Proprioceptive input from the moving limbs acts to influence the timing and amplitude of stepping while information from skin receptors is utilized to modify the stepping pattern in response to unexpected obstacles21. The control of gait is also highly dependent on supraspinal structures. The motor cortex, cerebellum, and several brain stem nuclei work to activate the CPG, to refine the motor pattern in response to peripheral feedback relayed via the cerebellum, and to guide movement according to visual input21. It is thought that human bipedal gait likely relies more heavily on descending systems and supraspinal

4 controls as compared to most quadruped animals due to the complexity of balance control16, 21. 2.2.2 Normal Gait Cycle A normal gait cycle, or stride, consists of the events which occur between two sequential points of initial contact of one lower extremity (LE)20, 24. A cycle consists of two steps, with each step defined as the sequence of events occurring from the point of initial contact of one foot to the point of initial contact of the other foot20, 24. Approximately 60% of the gait cycle is comprised of a stance phase wherein some portion of the foot is in contact with the ground24. The remaining 40% of the gait cycle is the swing phase during which the foot does not contact the ground at any time24. At the beginning and end of each gait cycle is a period of double support marking the transition between one stance limb and the other 24. These two periods of double support make up approximately 20% of the gait cycle20. The sequence of events that occur throughout a gait cycle begins at heel strike when the foot first makes contact with the ground. Heel strike is followed by foot flat where the foot is fully in contact with the ground. The limb then progresses into midstance at which point the contralateral LE is off of the ground and the body weight is directly over the supporting limb24. The body continues to progress forward over the stance limb through heel off as the foot of the supporting limb begins to leave the ground. The end of a normal stance phase is marked by toe off where only the toe of the ipsilateral LE is in contact with the ground 24. Once the toes have left the ground, the swing phase begins with acceleration. The LE continues to swing forward and reaches midswing when it passes directly under the body. The latter portion of the swing phase is called deceleration and is marked by the tibia moving beyond a vertical position and the knee is extended in preparation for the next heel strike20, 24. 2.2.3 Spatiotemporal Characteristics of Gait The characteristics of a gait cycle may be described on the basis of distance, time, or the interactions between these spatial and temporal parameters (also referred to as rate). Measures of rate include cadence and velocity. Cadence, or step frequency, is defined as the number of steps taken per unit of time and is usually noted in steps per minute 24. Gait velocity is the distance a person walks in a defined period of time. An individual may alter their velocity by changing their cadence or step length24.

5 During steady velocity walking, adults normally generate a cadence of 113 steps per minute17, 20. When velocity is kept constant, an individual can increase their cadence by reducing their step length24. Normal velocity for adults has been reported to range from 1.1 to 1.4m/s when a person is walking at a speed that they consider to be typical or comfortable20, 25. In 1997, Bohannon showed that normal gait velocity varies with age and gender26. He provided normative values for both males and females belonging to six different age groups at both comfortable and maximal gait speeds. The velocities of females walking at a comfortable speed ranged from 1.27 to 1.42m/s. Males aged 20 to 79 demonstrated gait velocities ranging from 1.33 to 1.46m/s when walking at comfortable speeds26. Spatial parameters of the gait cycle provide information about the linear distance between two points of contact in the gait cycle24. Step length is measured as the distance between the initial contact of one foot and the initial contact of the other foot 20 (see Figure 1). The average adult walks with a step length of approximately 0.60m when walking at a comfortable speed17, 25. Step width is the perpendicular distance between the point of initial contact of the left foot and the line of progression of the right foot, with the line of progression defined as the connecting line between two consecutive initial contacts of the same foot24, 27 (see Figure 1). Figure 1: Footfall Measurement Conventions (modified from GAITRite® Technical Reference)

Temporal parameters provide information about the duration of time spent within or between particular parts of the gait cycle. Stride time is the amount of time it takes to complete one stride, this duration is equivalent to that of the total gait cycle duration24. Step time is the period of time measured between two sequential points of initial contact of opposite extremities24. The duration of a particular phase of the gait cycle is often expressed as a percentage of the duration of the entire gait cycle. Stance time is the duration of time an individual spends with the foot in contact with the floor, from initial

6 contact to toe off24. The remainder of the gait cycle is spent in swing, the period between the foot leaving the ground and when initial contact is made24. The swing time of one LE is equivalent to the single support time of the opposite LE24. As previously mentioned, there are two periods of double support in which both feet are in contact with the ground. The percentage of time spent in double support decreases as speed increases24. 2.2.4 Symmetry of Gait Comparisons between the right and left lower limbs with respect to spatiotemporal, kinetic, and kinematic parameters are undertaken to determine the symmetry of gait. Under normal conditions, the spatial and temporal features of the gait cycle vary only slightly between the lower extremities and therefore human gait is considered to be largely symmetrical28. In able-bodied individuals, even variations in velocity do not significantly disturb the symmetry of the gait cycle29. Small inter-limb differences may be attributable to limb dominance18, 29 but the asymmetries reported are typically less than 6%28, 30. Symmetry measures identify the similarities between consecutive contralateral steps 31 and reflect interlimb control32. 2.2.5 Variability of Gait To the human eye, the cyclical gait pattern may appear highly stereotypical and extremely consistent. In fact, healthy adults demonstrate stride to stride fluctuations in both spatial and temporal parameters. Under stable environmental conditions, the amount of variability present is usually less than 5%33, 34. The presence of increased spatial and/or temporal variability may be indicative of disturbances in the neuromuscular control system and its ability to regulate gait33, 35, 36. More specifically, it identifies the similarities between consecutive ipsilateral steps31 and signifies intralimb control32. It is suggested however, that although variability is indicative of control, it is not reflective of an individual’s capacity to resist perturbation (ie not a measure of stability)37. Variability is present in the spatial features of gait including step length and step width. Spatial, or step length variability is related to the automaticity of walking and shows no age-related differences among healthy adults38, 39. Although step length variability may be influenced by reduced velocity40, an increase in step length variability should be considered indicative of gait pathology and may be useful as a predictor of individuals at risk of falling41. Balasubramanian et al (2009) suggest that severely impaired individuals may demonstrate between-leg differences in step length variability (i.e. an asymmetry of

7 step length variability) although the authors do not describe the degree of this asymmetry36. Step width variability is considered to be a gait characteristic which is related to balance control42. As a result, a great deal of research has been focused on determining how step width variability may be utilized as a marker of fall risk, especially among the elderly. Step width variability has been shown to be significantly greater among healthy older adults as compared with healthy younger adults38-40. In addition, studies have shown that step width variability may be used as a predictor of falls among ambulatory older adults and that both inadequate and excessive step width variability is associated with a history of falls 41, 42. These findings suggest that reduced step width variability may be indicative of a reduced capacity to modify step width appropriately for balance maintenance while increased step width variability may point to a diminished ability to control foot placement or center of mass displacement41, 42. Temporal variability, specifically stride or step time variability, is related to the control of rhythmic stepping43. It has been shown to be uninfluenced by age among healthy ambulators39 but that an increase in step time variability in the same population can be explained in part by decreased velocity40, 43, 44. Temporal variability during gait has been shown to be significantly influenced by attentional demand, indicating that in older adults the control of rhythmic stepping requires the involvement of higher cortical areas44. Increased step time variability has also proven useful as a predictor of falls in the elderly41, 45.

Less commonly described measures of temporal variability include the variability of the length of time spent in a particular phase of gait. For example, swing time variability and double support time variability have been described as measures with the potential to identify individuals with impaired sensorimotor feedback and balance control issues respectively41, 45. In general, among healthy normals, temporal variability is smaller than spatial variability34. 2.3 Post SCI Gait 2.3.1 Walking Function post-SCI The achievement of some level of ambulatory status within one year following iSCI has been reported to occur in 33 to 100 percent of patients12, 14, 46, 47 48-51. Many factors influence the walking function achieved by individuals following an SCI. These include, but are not limited to, the person’s age, motivation, level of physical

8 conditioning, and severity of neurological impairment12, 52-55. Barbeau et al. (2006) highlighted six determinants that they considered to have the most impact on walking postiSCI: (1) balance and posture, (2) range of motion, (3) muscle strength, (4) coordination/motor control, (5) muscle tone, and (6) sensation and proprioception12. Lower extremity strength in particular has been shown to be positively correlated with measures of functional walking performance46, 53, 56-58. In a study of patients with subacute iSCI, Wirz and colleagues (2006) demonstrated that AIS motor scores and locomotor function are closely related46. Among subjects with chronic SCI, the strength of the less affected hip flexors and hip extensors were strongly correlated with speed and ambulatory capacity respectively46. In an investigation of the walking abilities of subjects with NTiSCI, Sturt et al (2009) reported that 48% were ambulatory at the time of discharge from inpatient rehabilitation 47. The authors noted that both mean walking speed and mean distance achieved by these subjects were low (10mWT=0.33m/s; 6MWT=220m) as compared with normals47. Lapointe and coauthors (2001) found that with respect to speed, distance, and ability to navigate obstacles, almost 90% of subjects with iSCI did not achieve the functional level of ambulation necessary for independent community mobility following inpatient rehabilitation52. The study also confirmed findings by Waters et al that showed that subjects with iSCI have a higher rate of energy expenditure than healthy subjects walking at the same velocity52, 54. A 2003 study demonstrated that the capacity of low severity (AIS D) iSCI subjects to adapt to changes in treadmill speed was limited and related to their neurological deficits59. 2.3.2 Recovery of Walking post SCI The likelihood for patients classified as AIS A to achieve any level of walking has been reported to be as low as two percent55, 60. Patients with incomplete injuries have significant and variable potential to recover walking function46, 61. The rate of this recovery is highest in the first 6 months following the onset of iSCI46, 49, 50. The onset of walking ability among patients with iSCI has rarely been studied. A group of subjects with NTiSCI were able to complete the TUG, 10mWT, and 6MWT at a median of 67, 68, and 57 days post SCI onset respectively, suggesting that the commencement of functional walking is not likely to occur before two months after injury47. With intensive training, subjects classified as AIS C or D have demonstrated remarkable improvements within 12 weeks of rehabilitation (~16.5 weeks post onset)48. Wirz and coauthors showed

9 that patients with motor incomplete injuries significantly improve with respect to gait speed and WISCI scores by 6 months post injury46. The ability to predict which patients will or will not walk following iSCI is considered to be of critical importance to patient care51, 53, 61. Early longitudinal studies by Waters et al (1994) revealed that patients with TiSCI who have a LEMS of greater than 10 at one month post injury and hip flexion or knee extension strength of grade 2 or higher should be expected to achieve community ambulation status by one year post injury49, 50. All patients with a LEMS of 20 or more at the one month post injury time point are predicted to progress to become community ambulators within one year of injury62. Waters and colleagues also demonstrated that LEMS is positively and linearly related to both velocity and cadence such that these outcomes can be predicted using a simple mathematical equation 53. AIS classification has proven useful in the prediction of motor recovery as prognosis increases with successive grades A through D62, 63. Crozier and colleagues (1991) studied 27 patients classified as AIS B and determined that those with preservation of pin prick sensation below the level of injury were significantly more likely to recover the ability to walk by discharge from inpatient rehabilitation64. Kay et al (2007) retrospectively investigated the impact of AIS classification and age on the walking outcomes of subjects with TSCI at the time of discharge from inpatient rehabilitation. The authors concluded that by discharge 28.3% of patients classified as AIS C were able to walk with moderate assistance or less, that subjects with motor incomplete paraplegia and tetraplegia were equally likely to walk at discharge55, and that having an age greater than or equal to 50 years negatively affects the likelihood of walking among patients classified as AIS D 55. These findings support earlier research of subjects with traumatic motor incomplete SCI which showed that the prognosis for the recovery of walking by discharge from inpatient rehabilitation is very good (80.0% of study subjects were able to walk at least 50 feet without physical assistance) but that patients with AIS C tetraplegia who are over the age of 50 are significantly less likely to achieve the same functional level51. Zorner et al (2010) studied sub-acute patients with AIS C or D classification and developed four clinical algorithms for the prediction of independent and functional walking (defined as having a WISCI score of 20 and the ability to walk at a velocity of > 0.6m/s on the 6MWT respectively)61. The authors determined that the best predictors of WISCI and 6MWT for patients with tetraparesis were the combination of LEMS plus somatosensory-evoked

10 potentials and the combination of LEMS plus AIS classification respectively. The combinations of LEMS plus pin prick preservation and LEMS plus age were the best predictors of WISCI and 6MWT respectively for patients with paraparesis61. Although not generalizable to the sub-acute population, the study of subjects with chronic SCI has revealed several predictors of walking function that warrant consideration. Kim et al (2004) used linear regression to show that hip flexor and extensor strength of the less affected limb were predictive of walking ability in subjects with chronic iSCI56. Scivoletto and coauthors (2008) reported that spasticity and proximal LEMS were identified as the best predictors of the TUG and the 10mWT while balance, spasticity, age, and UEMS were the best predictors of the 6MWT for 65 subjects with chronic SCI65. 2.3.3 Gait Rehabilitation Approaches Post SCI As the understanding of walking function and post-SCI neurological dysfunction has increased, so has the number of strategies available for the rehabilitation of locomotion4, 12. Rehabilitation approaches for the recovery of walking following an iSCI strive to exploit the plastic nature of the central nervous system through the introduction of task-specific activities that comply with the concepts of forced use, relevant afferent input, and proportional physical demand12, 60, 66. The methods employed in attempt to facilitate the recovery of walking ability in patients with iSCI have included: conventional physical therapy, use of orthoses, body weight supported training (treadmill and over ground), robotic-assisted locomotor training, and functional electrical stimulation4, 14, 67. A systematic review conducted by Lam and colleagues (2007) suggests that there is strong evidence to support the application of intensive and repeated practice of gait via body weight supported training and/or functional electrical stimulation as a means of enhancing functional ambulation in subjects with sub-acute iSCI67. However, the results of a large multi-centre randomized control trial and the findings of a recent Cochrane Review indicate that no single approach to gait training is superior to another14, 48. Currently, the most clear indication from the literature is that the walking performance of subjects with sub-acute iSCI is enhanced with locomotor training, regardless of the specific approach utilized48, 68.

2.3.4 Spatiotemporal Profile of post-iSCI Gait The spatiotemporal characteristics of the gait of patients with iSCI have not been abundantly reported. In general, post-iSCI gait is characterized by reduced velocity52 56, 59,

11 69

and cadence70, as well as altered phase durations and step length59, 71. In addition,

subjects with iSCI also show a high degree of between-subject variability52, 68, 71. The mean walking velocity for patients with sub-acute iSCI has been reported to be as low as 0.34m/s (±0.38)47 and as high as 1.08 m/s (±0.06)72. Comfortable over-ground walking speeds for subjects with chronic iSCI have been reported to range from 0.11 to 1.76 m/s52, 56, 68, 71

with well-recovered subjects (AIS D) demonstrating velocities that do not

significantly differ from normals73. Subjects with low severity, chronic iSCI demonstrate significantly longer double support73, stance, and swing phase59, 71 durations as compared to normal controls during treadmill walking. 2.3.5 Symmetry of post-iSCI Gait Reports of altered symmetry post-iSCI have been limited to descriptions of the symmetry of sensorimotor function or lesion level56, 70, 73, 74. Field-Fote et al (2005)68 and Amatachaya et al (2009)75 used step length symmetry as an outcome measure for their studies investigating the differences in outcomes achieved using four different locomotor training methods in subjects with chronic iSCI. Unfortunately, the authors only reported the improvements in symmetry experienced by the treatment groups68, 75 and the later study does not describe the methodology used to calculate step length symmetry75. As a result, our understanding of spatial symmetry in the walking of subjects with chronic iSCI is limited to the graphic representations available which indicate that these subjects do present with mild to moderate step length asymmetry68, 75. 2.3.6 Variability of post-iSCI Gait A search of the literature (search terms: spinal cord injury, walking/gait, variability; limits: English, human) revealed that the study of gait variability in human subjects with iSCI has been limited to investigations of how robotic devices might ensure that some variability in stepping is maintained during robot-aided treadmill training76, 77. No studies were found that included reports of descriptive gait variability data for subjects with sub-acute iSCI. 2.3.7

Clinical Measures of Gait in SCI 2.3.7.1 Measures of Performance The Ten Metre Walk Test (10mWT) is a simple outcome measure used to assess short-distance walking speed which has been utilized for gait analysis in many neurological populations78-80. The middle ten metre section is timed as test participants walk over a 14m long level surface79. Owing to the inherent

12 requirement that a subject be able to complete the total distance of more than ten metres (a flying start and finish are recommended), the 10mWT has a floor effect78, 79. The 10mWT has been widely utilized as a measure of walking performance in the field of SCI study81 and has been shown to be a valid and reliable tool in the SCI population78. Good test-retest, intra, and inter-rater reliability have been shown for the 10mWT in the SCI population79, 81, 82. Construct and concurrent validity of the 10mWT have been demonstrated to be strong through comparisons with other measures (LEMS, 6MWT, TUG, WISCI)79, 81, 83. The Six Minute Walk Test (6MWT) was initially developed as a measure of aerobic capacity for cardiorespiratory patients84 has been extensively studied across many patient populations78, 79, 85, 86. The self-paced test requires that a subject walk as far as possible within the six minutes allowed84. In its application with subjects with SCI, the 6MWT has demonstrated good test-retest and interrater reliability69, 78, 79, 81, 83, 87 and studies have shown that it also has very strong construct and concurrent validity78, 79, 81, 83. van Hedel and coauthors (2008) recommended that the test be performed along a track which allows for as few turns as possible in order to minimize the influence of this particular balance challenge on the distance outcome78. The Timed Up and Go (TUG) is a measure designed as a screening test to assess the basic functional mobility of frail elderly individuals88. The TUG involves the measurement of the time (in seconds) required by a subject to rise from a chair, walk three metres, turn 180 degrees, and return to the seated position in the chair88, 89. Since its development the TUG has been used in the SCI population as a functional measure of walking performance and has been shown to have excellent test-retest and inter-observer reliability81, 83, 88. In addition, the TUG has excellent construct validity when compared to other timed measures of ambulation81, 83. 2.3.7.2 Categorical Measures The Assistive Devices Score (ADS) was developed as part of the Spinal Cord Injury Functional Ambulation Inventory (SCI-FAI)90. The SCI-FAI has demonstrated reliability, validity, and is a sensitive observational gait assessment tool designed explicitly to measure walking function in individuals with SC91, 92.

13 The ADS component of the SCI-FAI specifically measures the use of orthoses and assistive devices for ambulation. The AD score has been found to have 100% inter-observer agreement90. The Walking Index for Spinal Cord Injury II (WISCI) was specifically developed to evaluate the walking capacity of research subjects with SCI by determining their level of dependence on physical assistance, walking aids or braces when ambulating a distance of ten metres79. Subjects are rated on a 21-level hierarchical scale where a higher rating is indicative of lower levels of impairment79, 81. Studies have shown that the WISCI has excellent inter-observer reliability79, 81, 92, 93 and it has demonstrated criterion and concurrent validity79. Unfortunately, the WISCI does have significant floor and ceiling effects81 limiting its utility for the assessment of severely or mildly impaired SCI subjects 93. Recent work undertaken by Marino et al (2010) showed that a self-selected WISCI score also has high reliability and may be less sensitive to patient-therapist interactions93. The Functional Independence Measure (FIM) is a multidimensional scale that assesses an individual in terms of burden of care and their functional ability during daily activities81, 94. Designed for use in all populations, the FIM consists of 18 items, each scored on a 7 point system (1-7) with higher scores indicative of higher levels of independence79, 94. While the FIM is not specific to the SCI population94, the Canadian Institute for Health Information requires that it be completed for all inpatient admissions, therefore it can be a useful tool for the description of the study population. In general, the FIM is a valid and reliable tool but it does lack specificity for the SCI population92, 94. The Walking Mobility Scale (WMS) was also developed as a part of the SCI-FAI. It uses five criteria to categorize an individual’s typical walking performance90. The criteria describe five levels of ambulation ranging from “Physiologic Ambulation” to “Independent Community Ambulator”. As previously mentioned, the SCI-FAI has good reliability and validity90 and the WMS itself correlated well with the qualitative “Gait Score” portion of the SCI-FAI90. 2.3.8 Spatiotemporal Measures The measurement of the spatiotemporal features of the walking patterns of subjects with iSCI may be achieved by numerous methodologies. Studies containing spatiotemporal

14 data report collection methods including: paper marking, visual observation with a stopwatch, video recording, electronic foot switches, three-dimensional motion analysis systems, and a custom-designed treadmill59, 95, 96. Due to evidence that visual observation is inadequately objective, the supplementary use of technologically advanced methods of gait analysis in the clinical setting has been endorsed80, 97. The GAITRite® Electronic Walkway (CIR Systems, Clifton NJ, USA) (hereafter referred to simply as the GAITRite®) records individual footfalls by localization of activated/deactivated pressure sensors which are arranged in a grid pattern with a spatial resolution of 1.27cm and which are sampled at a frequency of 80Hz96. Although technology-based, the GAITRite® is relatively clinician and patient friendly98. Studies using healthy normal subjects have shown that the GAITRite® has strong validity when compared with pencil-and-paper95, video based95, 99, foot switches99, and a threedimensional motion analysis system98, 100. The GAITRite® has also been demonstrated to be a valid tool for the measurement of both averaged and individual step parameters of older subjects following knee arthroplasty100. The test-retest reliability of the GAITRite® has been confirmed to be high following testing of healthy normals at various walking speeds99 or across a seven day time period101. Menz et al (2004) studied the test-retest reliability of the GAITRite® using young and elderly subjects and found that it has excellent reliability with the exception of the toe in/out and base of support variables96. The authors therefore recommend that these two variables be regarded with some caution when collected from an elderly population96. The reliability and validity of the GAITRite® as a tool for the assessment of adults with iSCI has not been established, however its use in the study of adults with other neurological conditions35, 36, 87, 102 would suggest the practice is acceptable. 3.0 Objectives Objective 1: To describe a population of ambulatory subjects with sub-acute incomplete spinal cord injury. Objective 2: To describe the degree of variation that exists when subjects are stratified into groups on the basis of clinical characteristics (diagnosis or etiology). Objective 3: To describe the degree of variation present when subjects are stratified on the basis of gait characteristics (variables that are related to key characteristics of walking: aid use, velocity, symmetry, variability). Objective 4: To make recommendations regarding future research.

4.0 Methods 4.1 Participants This study was approved by the Research Ethics Board at the Toronto Rehabilitation Institute. A sample of subjects with traumatic (TiSCI) or non-traumatic incomplete spinal cord injury (NTiSCI) was selected by convenience from an existing clinical database of GAITRite® measures. The data had been collected by the treating physiotherapist (PT) during the subject’s inpatient admission at Toronto Rehab’s Spinal Cord Rehabilitation Program (SCRP) during the time period spanning January 1, 2009 to September 30, 2009. Subjects from the sample who had a documented walking assessment completed within 10 to 365 days post onset of injury were included. Subjects were excluded if they had a diagnosis of complete spinal cord injury (SCI) recorded as AIS A as classified according to the American Spinal Injuries Association (ASIA) International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI). A total of 101 patients were screened for inclusion in the study. Following the screening, 49 patients were excluded: 28 patients had a date of onset more than 365 days prior to the collection of GAITRite® data, 9 patients did not have a diagnosis of SCI, 7 patients had never been admitted to inpatient services at the SCRP, and 5 had GAITRite® recordings which were corrupted (i.e. no data were recorded) (see Figure 2). Figure 2: Subject Information n=101 28 Chronic Included 52 33♂/19♀

Excluded 49

5 Data Error 7 Never IP 9 Non-SCI

Non Trauma 34 18♂ / 16♀ AIS: 1B / 3C / 30D

Trauma 18 15♂ / 3♀ AIS: 6C / 12D

7 - No aid

4 - No aid

5 - one cane

4 - one cane

3 – two canes canes 19 - walker

4 - two canes 6 - walker

4.2 Measures 4.2.1 Clinical & Functional Measures Information about each subject’s clinical and functional status at admission was abstracted from the health record (see Table 1). The measures collected were recorded either at admission to the SCRP or at baseline (the first identifiable measurement recorded by the 15

16 treating PT). The timing of administration of each of the measures was at the discretion of the treating PT and thus not standardized. Table 1: Clinical & Functional Measures Abstracted from Subjects' Health Records Name ISNCSCI Assessment: Lower Extremity Motor Scores (LEMS) Sensory Level Overall Neurological Level Ten metre Walk Test (10mWT) Modified Six Minute Walk Test (m6MWT) Timed Up & Go (TUG) Assistive Devices Score (ADS) Walking Index for Spinal Cord Injury (WISCI) Functional Independence Measure (FIM) Walking Mobility Scale (WMS)

Clinical & Functional Measures Description Standard approach to the classification of SCI Total motor scores for lower extremities in 5 key muscle groups Lowest level of normal sensory function on both sides Lowest level of normal motor and sensory function on both sides Time (s) required to walk 10m Distance walked in 6 minutes Time required to complete stand, walk 3m, turn 180º, walk 3m, & sit down Sum of scores (/14) for upper extremity and lower extremity assistive devices Measure of level of dependence during walking a distance of 10m (score 0-20) Multi-dimensional measure of burden of care (score 0-126) Score selected from list describing 5 different levels of typical walking performance

4.2.2 Spatiotemporal Measures Data collected by the treating PT using the GAITRite® Electronic Walkway for each subject were obtained in raw form. The standard of practice at the SCRP among the treating PT’s was to collect a minimum of 20 steps of data for each patient at their preferred or comfortable pace with or without a gait aid. The patients walked on level ground over the pressure sensitive mat measuring 3.66m in length and 1.22m in width. Patients initiated each trial several steps prior to the leading edge of the mat and completed each trail only after walking off of the end of the mat completely. The number of trials collected was dependent upon the number of trials required to collect at least 20 steps of data. The raw data from individual trails was edited to remove objects or footfalls created by a gait aid or supervising therapist and then averaged to determine the spatiotemporal variables for each participant. Measures of symmetry were calculated as a ratio of absolute right versus left limb using the averaged spatiotemporal data (marked with an asterisks* in 2). Measures of variability were calculated from raw data as a coefficient of variation (expressed as a percent) by determining the means and standard deviations of both step time and step length. The list of parameters collected and calculated using the GAITRite® data are listed in 2.

17 Table 2: Spatiotemporal Parameters Obtained for Analysis Name: Total Distance (m) Total Ambulation time (sec) Velocity (m/sec) Cadence (steps/min) Cycle time (sec) Stance time (%gait cycle) Swing time (%gait cycle)

Spatiotemporal Measures Definition: Total distance walked in ≥ 20 steps Total time required to complete ≥ 20 steps Total distance/total time (Number of steps x 1min) / total time Time taken to complete stance + swing phase

Duration of time spent with the foot in contact with the ground, from initial contact to toe off (stance time/cycle time x100%) Duration of time between the foot leaving the ground and initial contact (swing time/cycle time x100%)

Single support (%gait cycle)

Duration of time spent with only one foot in contact with the ground (single support time/cycle timex100%)

Double support (%gait cycle)

Duration of time spent with both feet in contact with the ground (double support time/cycle time x100%)

Step length (m) *Temporal stance symmetry *Temporal swing symmetry *Total temporal symmetry *Spatial step symmetry Step time variability (%CV) Step length variability (%CV)

Distance between point of initial contact of one foot and initial contact of the other foot Right stance time / left stance time Right swing time / left swing time Right swing time / right stance time Left sing time / left stance time Right step length / left step length (Standard deviation/mean step time) x 100% (Standard deviation/mean step length) x 100%

4.3 Data Analysis All statistical analyses were performed using SPSS software (version 19.0, Chicago, Illinois). Descriptive statistics were performed for all variables measured. Box plots of each of the clinical and spatiotemporal measures were visually examined to identify outliers. Due to the non-parametric nature of the data, Mann Whitney U or Kruskal-Wallis tests were performed to identify groups of subjects that differed significantly from one another. Spearman’s correlation coefficient () was used to quantify the relationship between each of the spatiotemporal variables. Significance was set a level of p≤0.05. The GAITRite® software system automatically calculates the spatiotemporal measures outlined in Table 2 with the exception of the symmetry and variability measures. The output from the application software was downloaded into a Microsoft Excel 2003

18 spreadsheet for further calculations. All values were averaged over the total number of steps collected. Gait symmetry ratios were calculated for each subject using the mean swing and stance values and the convention of right divided by left. For the purposes of statistical analysis, symmetry ratio values (right/left) that fell below 1.0 were converted to a value greater than 1.0 by calculating its differential from 1.0 and then adding 1.0 to the differential as follows: converted symmetry value = [1.0 – (right/left)] + 1.0. The symmetry ratios calculated are summarized in 2. Variability measures were calculated as the coefficient of variation (standard deviation/mean) and expressed as a percentage (%CV). A description of the methodology used to create the various subgroups is described below in the respective results section. 4.4 Results 4.4.1 Subjects Of the 52 subjects included in the study (33 men, 19 women), the range and median age were 20 to 78 years and 53 years respectively. Subjects had sustained either a NTiSCI (n=34) or a TiSCI (n=18) which resulted in tetraplegia in 17 subjects and paraplegia in 35 subjects. Each of the 52 subjects was classified by AIS using the ISNCSCI such that the population was comprised of 1 subject with AIS B, 9 subjects with AIS C, and 42 subjects with AIS D. During the collection of data on the GAITRite®, subjects were allowed to use a gait aid as necessary; 25 subjects used a walker, 7 subjects walked with two single point canes (SPC), 9 subjects used one SPC, and 11 subjects walked with no gait aid at all. 4.4.2 Clinical Measures A summary of results collected from clinical measures is available in Table 3 at the end of section 4.4.2. Lower Extremity Motor Scores (LEMS) were available for 48 of the 52 subjects (4 were unobtainable at the time of assessment due to restrictions such as lower extremity fixation devices). As per the guidelines from the ISNCSCI, the minimum and maximum possible scores on the LEMS are 0 and 50 respectively. The range, mean, and median LEMS in the study population were 0 to 50, 36.00 (±11.45), and 38.5 respectively. Only 15 baseline measures of the 10mWT were available. The range of walking speeds, as measured by the 10mWT, was 0.14 to 1.27 m/s with a mean speed of 0.60m/s (±0.30), and a median speed of 0.55m/s. A total of 19 6MWTs were collected at baseline showing a range of 24.0 to 355.0 metres, a mean of 195.11m (±103.54), and a median distance of 209.61m.

19 The baseline TUG was limited in availability to 12 subjects. The range, mean, and median TUG time were 8.89 to 131.0 seconds, 32.86 s (±34.04), and 18.96 seconds respectively. The ADS has a maximum achievable score of 14 with higher scores representing a lower level of reliance on assistive devices and orthoses. At baseline, 49 subjects had an ADS score ranging from 5 to 14, with a mean of 8.65 (±2.33) and a median score of 8. The WISCI scores, which increase in value from 0 to 20 with decreasing levels of walking impairment, showed a range of 1 to 20, a mean of 11.06 (±4.79), and a median score of 13 (a score of 13 indicates that the subject ambulated with a walker, no braces, and no physical assistance for 10m93). The FIM was collected on admission for all 52 subjects with a range of 47 to 118, a mean of 85.38 (±17.73), and a median score of 86. Due to variation in clinical practice, several of the clinical outcome measures showed low collection numbers at baseline. The WMS score is a categorical measure of function which increases in value from 1 to 5 as an individual’s independence increases. The range of baseline WMS scores for 49 subjects was 1 to 5 with a mean of 2.37 (±1.19), and a median score of 2 (a score of 2 indicates that the subject walks rarely in the home and never in the community90). A baseline WISCI (maximum score = 20) was collected for 49 subjects. (See Appendix A – 8.1.1). Table 3: Summary of Results from Clinical Measures Measure n Range Admission LEMS 48 0 – 50 Baseline 10mWT (m/s) 15 0.14 – 1.27 Baseline 6 Minute Walk Test (m) 19 24.0 – 355.0 Baseline TUG (s) 12 8.89 – 131.0 Baseline Assistive Devices Score 49 5 – 14 Baseline Walking Index for SCI 49 1 – 20 (/14) Admission FIM 52 47 – 118 Baseline Walking Mobility Scale 49 1–5

Median 38.50 0.55 209.61 18.96 8.00 13.00 86.00 2.00

Mean (±SD) 36.00(±11.45) 0.60(±0.30) 195.11(±103.54) 32.86(±34.04) 8.65(±2.33) 11.06(±4.79) 85.38(±17.73) 2.37(±1.19)

4.4.3 Spatiotemporal Measures A summary of results derived from spatiotemporal measures is presented in Table 4 at the end of section 4.4.3. Spatiotemporal measures were collected using the GAITRite® for all 52 subjects walking at their preferred speed with their preferred gait aid.

20 4.4.3.1 Velocity The average walking speed across 52 subjects was 0.62m/s with a standard deviation of 0.32. Velocities were highly variable, ranging from 0.13m/s to 1.45m/s with a median speed of 0.56m/s (see Figure 3). Figure 3: Velocity Distribution

4.4.3.2 Cadence On average, the subjects demonstrated an ability to generate a cadence of 75.88 steps/min (±24.62). The lowest step rate was 29.20 steps/min and the highest exceeded reported normals at 133.48 steps/min (see Figure 4). Figure 4: Cadence Distribution

4.4.3.3 Stance and Swing Time The stance and swing time parameters herein are reported as a percentage of the total gait cycle time (e.g. % of gait cycle = stance time / stance time + swing time).

21 Although non-parametric statistical analysis demonstrated no significant differences between the right and left values (p = 0.209 and 0.212 for stance and swing respectively), each of these parameters is reported below separately. The results for mean stance phase duration were 68.89%(±5.92) and 70.35%(±6.37) for left and right limbs respectively (see Figure 5). The mean left swing phase duration was 31.12%(±5.92) and the mean right swing phase duration was 29.65&(±6.37) (see Figure 6). Figure 5: Stance Time Distribution

22 Figure 6: Swing Time Distribution

4.4.3.4 Single and Double Support Time The single and double support phase results are also expressed as a percentage of the total gait cycle (%GC). Although non-parametric statistical analysis showed no significant differences between the right and left values (p = 0.244 and 0.377 for SS and DS respectively), each of these parameters is reported below separately. Double support time values are presented as a total of the two double support phases (leading and trailing) each limb participates in during one gait cycle. The average single support time across subjects was 29.67% (±6.35) and 31.11% (±5.91) for left and right limbs respectively (see Figure 7). Mean left double support time was 39.82% (±11.40) and similarly, mean right double support time was 39.53% (±10.92) (see Figure 8).

23 Figure 7: Single Support Time Distribution

Figure 8: Double Support Time Distribution

24

4.4.3.5 Symmetry A normal range for symmetry is reported to be a value between 0.9 and 1.186, 103. Using the stroke literature as a guide, for the purposes of this paper symmetry was considered to be present in any subject with a ratio value between 1.0 and 1.1103, 104.

A value of 1.0 represents complete symmetry whereas values that increase

from 1.0 represent greater and greater amounts of asymmetry. Temporal stance symmetry values describe the similarity between right and left stance times (measured in seconds) just as temporal swing symmetry values pertain to the relationship between right and left swing times. The subjects in this study had a mean temporal stance symmetry of 1.06 (±0.07) with a range from 1.00 to 1.25. Temporal swing symmetry had a larger range from 1.01 to 1.51 but showed a similar mean to temporal stance symmetry of 1.12 (±0.13) (see Figure 9). Figure 9: Temporal Symmetry Distributions

25 Total temporal symmetry is a method of representing the right to left symmetry of the proportions of swing and stance phases throughout the gait cycle (R Swing time/R Stance time : L Swing time/L Stance time)86. The average total temporal symmetry value for the 52 subjects included in this study was 1.17 with a standard deviation of 0.18. The total temporal symmetry values ranged from 1.01-1.63 (see Figure 10). Figure 10: Total Temporal Symmetry Distributions

Spatial step symmetry values describe the length relationship between the right and left steps. The mean spatial step symmetry was found to be 1.11(±0.13) with a range of 1.00 to 1.68 (see Figure 11). Figure 11: Spatial Symmetry Distribution

26 4.4.3.6 Variability For the purposes of this paper, variability is expressed as the percent coefficient of variation (%CV) and values greater than 5% are considered to represent individuals with greater than normal variability (based on reported normative values)33, 34. Both step time and step length variability are presented with separate left and right sided values as non-parametric statistical analysis showed that the spatial values were significantly different from one another (p = 0.43 for left versus right step length variability). The mean step time variability was 9.71% (±7.54) and 9.51% (±8.62) with ranges of 2.11 to 41.58% and 3.11 to 55.13% for left and right respectively (see Figure 12).

Figure 12: Temporal Variability Distributions

27 Step length variability was also generally high with left and right mean values of 9.43% (±6.56) and 8.45% (±5.11) respectively. The range for left step length variability was 2.27% to 42.95% while the right step length variability range was 1.71% to 24.40% (see Figure 13).

Figure 13: Spatial Variability Distributions

28 Table 4: Summary of Spatiotemporal Results Range

Parameter

Left

Velocity (m/s) Cadence (steps/min)

Median Right

Left

Mean (±SD)

Right

Left

Right

0.13-1.45

0.56

0.62(±0.32)

29.20-133.48

72.79

75.88(±24.62)

Stance Time (%)

60.78-86.57

60.75-87.15

66.93

68.65

68.89(±5.92)

70.35(±6.37)

Swing Time (%)

13.46-39.22

12.85-39.25

33.05

31.34

31.12(±5.92)

29.65(±6.37)

Single Support Time (%)

12.88-38.86

13.71-39.26

31.07

33.28

29.67(±6.35)

31.11(±5.91)

Double Support Time (%)

25.56-78.03

26.38-73.33

36.01

37.03

39.82(±11.40)

39.53(±10.92)

Temporal Stance Symmetry

1.00-1.25

1.03

1.06(±0.07)

Temporal Swing Symmetry

1.01-1.51

1.07

1.12(±0.13)

Total Temporal Symmetry

1.01-1.63

1.09

1.17(±0.18)

Spatial Step Symmetry

1.00-1.68

1.07

1.11(±0.13)

Step Time Variability (%CV)

2.11-41.58

3.11-55.13

7.74

6.55

9.71(±7.54)

9.51(±8.62)

Step Length Variability (%CV)

2.27-42.95

1.71-24.40

8.54

7.03

9.43(±6.56)

8.45(±5.11)

4.4.3.7 Correlations between spatiotemporal parameters It is known that many of the spatiotemporal parameters of gait are related to one another. In order to determine the strength of these relationships among the study population, a correlation analysis was completed. The results show that many of the spatiotemporal parameters are strongly correlated. A strong correlation is considered to be one with a coefficient of greater than or equal to 0.856. Specifically among the study subjects, velocity is strongly correlated with cadence (ρ=0.869), right stance time (%GC) (ρ= -0.892), and double support time (%GC) (ρright= -0.849, ρleft= -0.835). Stance time is also strongly correlated with swing time (%GC) (ρ=1.000) as well as both single (ρright= -0.988, ρleft= -0.996) and double support time (%GC) (ρright=0.883, ρleft= 0.887). (see Table 14 in Section 8.1.2). 4.4.4 Results Based on grouping by Clinical Characteristics Subjects with spinal cord injury are often stratified into groups on the basis of their clinical characteristics. Most commonly, comparisons are made between groups of subjects who share a common etiology of injury (non-traumatic or traumatic), a similar level of injury

29 (tetraplegia or paraplegia), or had a similar severity of injury (AIS C or AIS D). The results reported below use these three stratifications with summary tables presented in Appendix B. 4.4.4.1 Non-traumatic vs. Traumatic Etiology of SCI The etiology of each subject’s iSCI was identified through the chart abstraction process and subjects were identified as belonging to either the Traumatic or Nontraumatic group. The subject characteristics of each group are summarized in Table 5. Table 5: Summary of Etiology Group Characteristics Non-Traumatic SCI Traumatic SCI Total n 34 18 Male : Female

18 : 16

15 : 3

mean age (yrs) (p=0.001) Tetra : Para

56.82(±15.33)

41.11(±15.58)

7 : 27

10 : 8

AIS

1B : 3C : 30D

0B : 6C : 12D

19 walker : 3 bilat SPCs : 5 unilat SPC : 7 no aid

6 walker : 4 bilat SPCs : 4 unilat SPC : 4 no aid

Gait Aid

Analysis of the clinical measures data on the basis of subject grouping by etiology revealed no significant differences between the groups with the exception of the baseline TUG. Only a small number of TUG times were collected by clinicians at baseline for each of the etiology groups (NTiSCI n=9, TiSCI n=3). The range of TUG times were 13.7 to 131.00 for the NTiSCI group and 8.89 to 15.50 for the TiSCI group. The median and mean TUG times for NTiSCI subjects were 31.00 and 39.68(±37.16) respectively. The TiSCI subjects had median and mean TUG times of 12.81 and 12.40(±3.32) respectively. There was a significant difference in the distribution of TUG times (p=0.033), even when the major outlier was removed from the analysis (p=0.041). Similarly, almost all of the spatiotemporal variables showed that the etiology groups were not significantly different. Only in the case of right sided step length variability did the etiology groups significantly differ from one another (p=0.014) (see Appendix B - Table 15 & Table 16).

30 4.4.4.2 Level of Injury: Tetraplegia and Paraplegia Each subject’s neurological level of injury (LOI) was identified through the chart abstraction process from the available medical data. Subjects were subsequently categorized as belonging to either the Tetraplegia (injury level of C1 to T1) or Paraplegia group (injury level of T2 or below). The subject characteristics of each group are summarized in Table 6. Table 6: Summary of LOI Group Characteristics Tetraplegia Total n 17

Paraplegia 35

Male : Female

13 : 4

20 : 15

mean age (yrs) (p=0.441) NTSCI : TSCI

54.65(±13.33)

49.97(±18.45)

7 : 10

27 : 8

AIS

0B : 4C : 13D

1B : 5C : 29D

8 walker : 2 bilat SPCs : 3 unilat SPC : 4 no aid

17 walker : 5 bilat SPCs : 6 unilat SPC : 7 no aid

Gait Aid

As expected, analysis of the clinical measures data on the basis of subject stratification by level of injury (LOI) revealed that the distribution of LEMS differed significantly (p=0.025). The LEMS among subjects with tetraplegia (n=14) ranged from 24 to 50 with a median of 45.5 and a mean of 41.07(±10.13). The Paraplegia group (n=34) had LEMS range of 0 to 49 with a median of 36.0 and a mean of 33.91(±11.45). Otherwise, there were no significant differences between the LOI groups with respect to the clinical measures collected. Non-parametric analysis also showed that the LOI groups were not significantly different to one another in any of the spatiotemporal variables (see Appendix B - Table 17 & Table 18). 4.4.4.3 Severity of Injury: AIS C and AIS D The severity of each subject’s iSCI was identified through the chart abstraction process from the LEMS or manual muscle scores available. Subjects were identified as belonging to either the AIS C or AIS D group according to ISNCSCI

31 guidelines. Subjects with non-traumatic injuries were categorized as AIS C if greater than 50% of key muscles below the neurological level of injury were below grade 3 and as AIS D if more than 50% of key muscles below the neurological level of injury were grade 3 or higher. For the purposes of this thesis, the single subject with AIS B was not included in the description of the population or the comparative analysis. The subject characteristics of each severity of injury (SOI) group are summarized in Table 7. Table 7: Summary of SOI Group Characteristics AIS C Total n 9

AIS D 42

Male : Female

7:2

26 : 16

mean age (yrs) (p=0.892) NTSCI : TSCI

51.22(±16.10)

52.05(±17.22)

3:6

30 : 12

4:5

13 : 29

2 walker : 2 bilat SPCs : 2 unilat SPC : 3 no aid

23 walker : 5 bilat SPCs : 6 unilat SPC : 8 no aid

Tetra : Para Gait Aid

Analysis of the clinical measures data on the basis of subject stratification by severity of injury (SOI) revealed significant differences between the SOI groups in most cases. Since the LEMS is derived from a portion of the ISNCSCI which is used to categorize subjects into SOI groups, the results that follow were not surprising. The AIS C group had admission LEMS ranging from 13.00 to 24.00, with a median score of 20.0 and a mean score of 19.00(±4.24). LEMS for subjects with AIS D ranged from 25.00 to 50.00, a median LEMS of 41.00, and a mean LEMS of 39.88(±7.40). As expected, the distribution of LEMS was significantly different across the SOI groups (p=0.000). The baseline 6MWT, baseline WISCI, admission FIM, and baseline WMS all showed significant differences in their distributions when subjects with AIS C were compared with subjects with AIS D (p values = 0.025, 0.003, 0.003, and 0.002 respectively). In contrast, non-parametric analysis showed no significant differences between the

32 SOI groups with respect to any of the spatiotemporal variables (see Appendix B Table 19 & Table 20). 4.4.5

Results Based on Grouping by Gait Characteristics

Although not commonly executed, subjects with SCI can also be stratified into groups on the basis of the characteristics of their gait. The following sets of comparisons have been made between: (1) groups of subjects utilizing the same gait aid, (2) groups of subjects walking at similar velocities, (3) groups of subjects who have similar levels of symmetry (temporal or spatial), and (4) groups of subjects with similar levels of variability (temporal or spatial). The results are reported below using these four stratifications with a summary table presented in Appendix B. 4.4.5.1 Gait Aid Groups The gait aid used by each subject during the GAITRite® assessment was identified from the clinical database. If the aid used was not documented, the raw footfall graphics were examined to confirm which gait aid, if any, was used by the subject. Subjects were subsequently categorized according to the gait aid used during the GAITRite® collection. The subject characteristics of each group are summarized in Table 8. Table 8: Summary of Gait Aid Group Characteristics Walker 2 Canes Total n

1 Cane

No Aid

25

7

9

11

Male : Female

12 : 13

6:1

7:2

8 :3

mean age (yrs) (p=0.918) NTSCI : TSCI

52.96(±16.86)

52.71(±17.39)

48.78(±17.43)

49.63(±18.54)

19 : 6

3:4

5:4

7:4

8 : 17

2:5

3:6

4:7

2C : 23D

2C : 5D

2C : 6D*

3C : 8D

Tetra : Para AIS

*the single AIS B subject would have belonged to the 1 Cane group

Analysis of the clinical measures data on the basis of subject stratification by gait aid revealed no significant differences between the groups for any of the

33 measures. In contrast, almost all of the spatiotemporal variables did show that the gait aid groups significantly differed from one another. Only in the cases of temporal and spatial measures of symmetry did the gait aid groups not significantly differ from one another (see Appendix B - Table 21 & Table 22). In addition to the analysis above, a more detailed look at the “No Aid” group is warranted as this group’s results were not influenced by their use of a gait aid. These 11 subjects were stratified into groups using the same methodologies as were used for the total study population previously. When etiology groups were compared, they were found to differ significantly only with respect to their Admission FIM scores (mean FIM for TiSCI= 91.71(±12.88), mean FIM for NTiSCI=65.25(±13.70), p=0.014) but showed no differences in any of the other clinical measures or any of the spatiotemporal measures. Analysis revealed that a comparison of clinical measures between Level of Injury groups yielded no significant findings. In fact, among the spatiotemporal measures, the only parameters which were significantly different between LOI groups were Right Stance Time (%GC) and Right Swing Time (%GC) (p=0.038 in both cases). When the “No Aid” group were separated by severity of injury, the groups were found to differ significantly with respect to LEMS (p=0.015), ADS (p=0.031), WISCI (p=0.018), and WMS (p=0.012). None of the spatiotemporal measures showed that there were significant differences between the SOI groups. The “No Aid” subjects did not include anyone that walked at a velocity of less than 0.35m/s. The ten subjects were stratified into the remaining velocity groups with a notable bias towards the Moderate Velocity group (n=7). Analysis of the available clinical measures revealed that the velocity groups did not differ significantly from one another however, among the spatiotemporal variables, both Double Support Time (%GC) (p=0.026) and Right Temporal Variability (p=0.044) showed significant differences. Stratification of the “No Aid” subjects into temporal or spatial symmetry groups did not create significantly different groups across any of the clinical measures or spatiotemporal parameters. With respect to clinical measures, neither temporal nor spatial variability stratification showed the subjects

34 who walked without an aid were significantly different to one another. When the temporal variability groups were compared, they differed significantly only in spatial variability findings (p=0.017). Similarly, when the “No Aid” subjects were divided into spatial variability groups, they differed significantly only with respect to Left Temporal Variability (p=0.043) (see Appendix B - Table 23 & Table 24). As was the case for the entire study population, many of the “No Aid” group’s spatiotemporal parameters were correlated. Specifically, velocity was strongly correlated with cadence (ρ=0.800) while stance time (%GC) and swing time (%GC) were very strongly correlated (ρ=1.000). Stance time (%GC) was also strongly correlated with left single support time (ρleft=0.845, ρright= -0.973) and right single support time (ρleft= -0.945), and both temporal variability (ρleft=0.809), and spatial variability (ρleft=0.809). Left swing time (%GC) was strongly correlated with left and right single support time (ρ= -0.845, and ρ= 0.945 respectively) while right swing time (%GC) was strongly correlated with left single support time (ρ=0.973). Right single support time was strongly correlated with both temporal and spatial variability on the left (ρ= -0.873, and ρ= -0.818 respectively). Temporal stance symmetry and temporal swing symmetry had a correlation coefficient of 0.864 and left temporal variability was strongly correlated with both left (ρ=0.891) and right (ρ=0.800) spatial variability (see Appendix B - Table 25). 4.4.5.2 Velocity Groups The study population was divided into four velocity groups: Extremely Slow (ESv) (velocity 10%). The creation of the 3 variability groups was based on normative values which indicate that variabilities of less than 5% are expected among healthy normals33, 34, 43. Step variabilities of greater than 10% have been shown to be related to conditions in which subjects are particularly challenged35, 43, therefore 10% was selected in the current study to delineate subjects with moderate and high levels of variability. The subject characteristics of each Temporal Variability group are summarized in Table 12. Table 12: Summary of Temporal Variability Group Characteristics Low Moderate Total n

High

7

30

15

Male : Female

4:3

19 : 11

10 : 5

mean age (yrs) (p=0.081) NTSCI : TSCI

43.43(±21.66)

49.53(±15.75)

59.20(±15.11)

4:3

17 : 13

13 : 2

2:5

11 : 19

4 : 11

2C : 5D

6C : 23D*

1C : 14D

Tetra : Para AIS

*the single AIS B subject would have belonged to the Moderate group

Analysis of the clinical measures data on the basis of subject stratification by temporal variability revealed no significant differences between the groups (see Table 32). In contrast, the temporal variability groups were significantly different from one another across nearly all of the spatiotemporal parameters. Only in the cases of temporal swing symmetry and spatial symmetry were the temporal variability groups not significantly different (see Table 33).

38 The study population was also divided into three spatial (ie step length) variability groups: Low (variability = 0-5%), Moderate (variability = 5.1 – 10%), and High (variability >10%) (rationale for category thresholds as per temporal variability above). The subject characteristics of each Spatial Variability group are summarized in Table 13. Table 13: Summary of Spatial Variability Group Characteristics Low Moderate High Total n

9

29

14

Male : Female

5:4

18 : 11

10 : 4

mean age (yrs) (p=0.003) NTSCI : TSCI

36.11(±15.27)

51.31(±16.51)

61.79(±10.96)

4:5

19 : 10

11 : 3

2:7

9 : 20

6:8

3C : 6D

4C : 24D*

2C : 12D

Tetra : Para AIS

*the single AIS B subject would have belonged to the Moderate group

Analysis of the clinical measures data on the basis of subject stratification by spatial variability revealed no significant differences between the groups (see Table 34). The spatial variability groups were however significantly different from one another across nearly all of the spatiotemporal parameters with the exception of temporal and spatial symmetry (see Table 35). 5.0 Discussion 5.1 Total Population Overall, the description of the total study population reveals the considerable heterogeneity of impairment among study subjects with sub-acute iSCI. In general, the study subjects walked at very slow speeds with one or more gait aids and were considerably limited with respect to their overall walking function. These findings were not particularly unexpected for a cohort of subjects with iSCI participating in tertiary rehabilitation; as the gait of similar subjects with iSCI has been reported by multiple authors to be characterized by reduced speed, general dyscoordination, and limited independence56, 59, 74. The varied gait presentation of the study sample is also at least partially attributable to some practice variations amongst the treating physiotherapists responsible for the subjects’ rehabilitation.

39 The majority of the study subjects were classified as AIS D (80.8%), consistent with the relatively high mean LEMS (36.0/50.0) indicating that the cohort as a whole should be considered to be “motor functional”63. As early LEMS (i.e. within 1 month of SCI onset) are highly predictive of walking function outcome49, 50, 53, the results would suggest that the majority of the study subjects would achieve functional ambulatory status at one year post onset61. However, it should be noted that despite the predictive abilities of LEMS, an increase in LEMS is not always associated with a higher level of walking function46. Subjects from the current study demonstrated a wide range of outcomes in the timed clinical measures (10mWT, 6MWT, and TUG). A degree of the variation may be explained by the inconsistent time points of data collection; however these measures are indicative of global walking function rather than specific walking impairment(s)78, 79. The 10mWT is a useful measure of the overall quality of gait, but can be difficult to interpret61, 107. Subjects with iSCI studied by Lapointe et al (2001)52, showed that they lacked the ability to meet community ambulation requirements (thresholds reported to be 1.06m/s and 342m52). This is consistent with the current study population who achieved an average walking speed of only 0.60m/s (±0.30) (as measured by the 10mWT) and an average 6MWT distance of just 195.11m (±103.54). Similarly, Sturt et al (2009) reported that subjects with sub-acute, non-traumatic iSCI performed the TUG in an average of 33.0s (±21.0) at discharge from inpatient rehabilitation. The current study findings support the authors’ conclusions that the average TUG time of subjects with iSCI is generally twice that of community-dwelling older adults47, 88. The average walking distance achieved by the current study population was markedly below established community mobility requirements52 but was similar in value to previous reports47. The high degree of heterogeneity in walking function remained apparent when the results of the categorical clinical measures (ADS, WISCI, FIM, and WMS) were explored. In general, the majority of subjects required the use of assistive devices to achieve limited walking function. The average ADS score of 8.65 (±2.33) is difficult to interpret as the score is achieved by summing the UE devices and LE devices scores. The ADS findings do however correspond to those reported by Field-Fote et al (2001)90 who determined that 22 subjects with iSCI (of unknown acuity) had a mean ADS of 7.68 (±2.57). Also consistent with the current study, research investigating ambulatory status in sub-acute iSCI subjects has shown that a WISCI score ranging from 0 to 20 is common for this population108. van Hedel and coauthors have noted that only a small number of WISCI categories are actually required to categorize a large proportion of ambulatory iSCI subjects indicating that the tool may have some inherent redundancy78.

40 Two of the categorical measures included in the current study were the FIM, a measure of burden of care94, and the WMS, a scale which describes typical walking performance90. The FIM Locomotor score, a subscale of the FIM used to isolate information about a person’s locomotory function, was not utilized in the current study as it has been shown that it lacks validity and has poor reliability60, 79, 81, 91. The average total admission FIM score of 85.38 (±17.73) is slightly higher than those reported by Guilcher et al in 20107 whose data (n=1562) includes FIM scores collected on patients with complete SCI. At baseline, the subjects from the current study were assessed on average to be “able to walk in the home but limited by endurance, strength, or safety”90 according to the WMS (mean=2.37±1.19). This finding is not dissimilar to a 2001 report that found the average WMS score for a group of subjects with iSCI to be 2.77 (±1.27). The lack of available data for many of the clinical measures (~ 70% missing data for 3 timed measures of walking) points to the need for increased standardization of data collection at the point of care; not only with respect to the standardized method of collection, but also the standardization of time points for collection. Specifically, the timed measures of walking function (10mWT, 6MWT, and TUG) were available for less than 50% of the total study sample. One might consider two possible reasons for the observed poor measurement adherence: (1) that the patients were perceived by the therapists to be unable to complete the walking distance required by the measure and/or (2) that the perceived clinical value of the data obtained from these measures is low and therefore collection was considered unimportant. Regardless of the reason, the lack of complete data sets necessitates an improved understanding of the barriers to collection of walking measures in the clinical environment. The spatiotemporal values collected and calculated for the total study population showed a high degree of variation and in most cases were not normally distributed. In general, the subjects’ velocity across the GAITRite® was slow (mean=0.62m/s ±0.32), a speed which is considered to be non-functional for a community living environment52 and a cadence (mean=75.88steps/min ±24.62) that is almost 30% below accepted norms17, 25. With respect to phases of the gait cycle, the current study subjects spent longer periods of time in stance phase with a large proportion of that stance phase spent in double support as compared with able bodied peers. An increased DS time is common after iSCI and has been observed even in subjects with chronic iSCI of low severity (AIS D) and high LEMS who walk without the use of aids73. The double support phase is thought to be one which requires less balance and muscle strength and so an increase in duration may be indicative of a motor abnormality even in the

41 absence of any perceptible functional deficit73. Specifically, an increased DS duration in the iSCI population could signify aberrant balance control mechanisms or a reduced capacity to generate rapid alternating stepping movements71. However, it is important to acknowledge that in normal walking it is known that spatiotemporal parameters are influenced by walking velocity17, 25, 74, 109 and that in general, stability decreases with decreased velocity43, 109. Therefore, it is reasonable to consider that the increased DS percent seen in the current study population can be at least partly explained by the slow velocities adopted by these subjects59. Interestingly, the subjects did show DS durations which were on average significantly above normal (mean L DS=39.82%(±11.40); mean R DS=39.53%(±10.92)) despite the use of gait aids which would be expected to attenuate balance control issues70, 110. It is possible then, that the degree of increase in DS would have actually been higher had subjects been asked to walk without an aid during data collection. The question of whether the gait characteristics of subjects with iSCI are simply attributable to their reduced walking speed was in part addressed by a study by Pepin and colleagues (2003) who investigated the abilities of subjects with iSCI to adapt their walking patterns to changes in treadmill speed59. The authors determined that the walking patterns demonstrated by subjects with iSCI cannot be explained by reduced speed alone and that they are also result from the subjects’ neurological deficits 59. Overall, the mean symmetry values of the study subjects fell slightly outside of normal values (mean total temporal symmetry = 1.17 ±0.18, mean spatial step symmetry = 1.11 ±0.13) indicating that for the majority of subjects a lack of symmetry was not a major contributor to their overall gait presentation. Alternatively, one may conclude that the finding of minimally abnormal symmetry ratio values is indicative of subjects with symmetrical impairments as opposed to a lack of impairment with respect to interlimb coordination111. Measures of symmetry may be more applicable to subjects who present with significantly asymmetric motor and sensory dysfunction112. In fact, in most cases, subjects in the study population who were found to have severely asymmetric gait also presented with marked asymmetry in their LEMS. Field-Fote et al (2005) included a measure of spatial symmetry in a study which investigated the outcomes related to different walking intervention methods for subjects with iSCI68. The reported values appear to be consistent with the current study finding that subjects with iSCI are most likely to exhibit asymmetry but not severe asymmetry. Among normal individuals, studies have shown that symmetry is largely maintained across a variety of velocities29 although the slowest tested velocities are often greater than those achieved

42 by neurologically impaired individuals. In other neurological populations, a weak relationship has been shown between spatial asymmetry and walking speed indicating that walking speed is not likely to be strongly influenced by spatial asymmetry103. However, studies of stroke survivors with unilateral lower limb deficits have shown that subjects who walk at speeds below 0.60m/s are more likely to have severe temporal asymmetry104. In the current study, the influence of velocity on symmetry outcomes cannot be overlooked as a possible confounding factor. The study population findings indicate that subjects with sub-acute iSCI have greater than normal levels of temporal and spatial variability (with normal defined as 0.80). Interestingly, neither symmetry nor variability was found to be strongly correlated with other spatiotemporal variables. In contrast to the findings of Danion and coauthors who studied stride variability in normals34, the current study showed only a moderate association

43 between spatial and temporal variability. Velocity showed a moderately strong relationship with variability indicating that these two parameters may influence one another, especially when the gait aid influence is eliminated. The description of the study sample has not assisted in clearly identifying walking onset. Although not an objective of the study, identification of the time point when walking began for each subject was expected to be apparent. In order to mark walking onset on an individual basis, several conditions must be met. Firstly, a clear definition of what is to be considered walking must be created. One example of a definition of walking is: the ability to travel 10 metres across a flat surface via a stepping pattern with or without the assistance of an external aid but without the physical assistance of another person. Second, the measurement of walking, whether clinical or spatiotemporal, must be initiated prior to the achievement of walking as per the aforementioned definition. Measures that are likely feasible for collection with “pre-ambulatory” subjects include the LEMS, TUG, velocity, and other spatiotemporal parameters that require a minimal number of steps rather than a minimal distance (such as gait phase durations). Lastly, in the case of data captured by clinicians, it is crucial to understand the factors that influence a clinician’s decision to “allow” a patient to attempt walking. It is possible that these factors have the highest degree of influence on which walking measures are collected and when they are collected. Despite the limitations in data availability and perhaps quality, the description of the total study population clearly shows that subjects with sub-acute iSCI are a very heterogeneous group with respect to both their impairments, walking ability and gait features. 5.2 Subgroups The division of subjects into groups according to some commonality has been utilized in the past in an attempt to identify subgroups that have clinically important differences in their prognoses or treatment needs115, 116. In subjects with iSCI, it has been suggested that stratification of subjects into groups on the basis of their predicted walking outcome would be beneficial in the study of interventional therapies61. Unfortunately, the suggested variables (e.g. LEMS, AIS) have been used to predict walking function as measured by relatively global measures of walking function (e.g. WISCI, 6MWT)61 as opposed to measures which might be more closely related to the sensorimotor control of walking (i.e. spatiotemporal parameters). Field-Fote (2005) and coauthors encouraged fellow SCI researchers to consider subject sub-

44 grouping as an important aspect of interventional study design and predicted that further work would demonstrate that certain locomotor functions would be preferentially influenced by particular interventions68. The authors of a 2008 Cochrane Review on locomotor training after SCI also proposed that the reason for their inconclusive results might be linked to the inability to characterize the SCI population beyond AIS and lesion level14. They proceeded to recommend that sub-populations should be investigated in order to determine who would most benefit from particular intervention approaches14. Although the best method of subgroup identification may be derived through clinical prediction studies117, an evaluation of cross sectional data to screen variables with the potential to distinguish distinct subgroups is a rational initial step. The second and third objectives of this paper were aimed at describing the degree of variation that exists when different variables were utilized to generate subgroups. 5.2.1

Clinical Subgroups Etiology: It is common to describe the differences among subjects with respect to their prognoses or outcomes according to the etiology of their iSCI and significant differences between these groups have been reported. It is recognized that patients with NTiSCI are more likely to be older, have a lesser severity of injury, and achieve a higher degree of functional walking ability than those with TiSCI 7, 47, 58, 118, 119.

It has also been clearly demonstrated that patients with NTiSCI are

more likely to have comorbidities that complicate their clinical presentation and therapy delivery7, 58. The age, gender, level of injury, and AIS distributions of the NTiSCI and TiSCI groups in the current study are similar to those reported by other authors7, 47, 58, 118. The comparison of etiology groups in the current study showed that individuals with TiSCI were largely similar to those with NTiSCI in regard to both clinical measures and spatiotemporal parameters of gait. With respect to clinical walking measures, the results for subjects with NTiSCI reported by Sturt et al (2009) were similar to those found for the same etiology group herein47. In contrast to the current study, Guilcher and coauthors found that within a large study sample (n=1562), subjects with NTSCI had significantly higher admission FIM scores than those with TSCI7. The current study population did not include subjects with complete SCI and this has perhaps contributed to the lack of

45 significant difference found between etiology groups with respect to admission FIM scores (p=0.456). Unfortunately, very little research exists which examines the impact of etiology on the spatiotemporal features of the gait of subjects with iSCI specifically. Research that has included an investigation of spatiotemporal parameters is limited to the study of subjects with traumatic etiology only59, 68, 73, 110. The findings of the current study show that the distributions of spatiotemporal variables for subjects with NTiSCI as compared to subjects with TiSCI are similar and overlapping. The results also indicate that the degree of variation within each etiology group is likely too high to result in meaningful distinctions for the purposes of understanding gait characteristics. LOI: Another common means of distinguishing groups of subjects is to divide them according to the neurological level of their injury (i.e. paraplegia vs. tetraplegia). The proportion of subjects with paraplegia (67.4%) in the current study is higher than reported by authors of epidemiological studies7, 8, 120, 121. The disproportionate size of the paraplegia group could be due to the selection of subjects from an existing database generated by the treating PT’s who may have been more likely to collect data on patients with paraplegia than tetraplegia. It is also plausible that the distribution of patients admitted to the rehabilitation program was skewed during the selected time period. The group of paraplegics in the current study also had a higher proportion of subjects with non-traumatic etiology (77.1%) than the group with tetraplegia (41.2%). This finding is supported by Cosar et al (2010) who suggest that subjects with NTiSCI are more likely to have paraplegia as the incidence of spinal tumors, which are more common in the thoracic spine, is the most common non-traumatic etiology among subjects with iSCI58. Functional differences between the LOI groups were expected as impairment in the upper extremities can have a significant impact on one’s ability to ambulate 54, and the choice of gait aid 65. In the present study, 76% of subjects with tetraplegia used a gait aid while 80% of those with paraplegia used a gait aid. This points to the likelihood that the degree of upper extremity impairment did not greatly influence the usability of a gait aid.

46 As in the present study, Wirz and coauthors (2006) reported that subjects with paraplegia and tetraplegia who achieve ambulatory status in the sub-acute phase demonstrate similar levels of function as measured by the WISCI and the 10mWT46. Similarly, an early study by Waters et al (1989) showed that gait velocity and energy expenditure were not related to level of injury54. Unfortunately, the ISNCSCI, which is used to determine LOI, does not include an evaluation of motor function throughout the thoracic region. As a result, our understanding of the impact of trunk impairment on walking ability remains largely based on clinical experience rather than research evidence. Consequently, although it is generally thought that trunk impairment significantly influences walking ability, we can only be certain that subjects categorized as having tetraplegia have significant trunk impairment. The degree to which a patient categorized as having paraplegia is affected throughout his/her trunk is limited to our knowledge of their sensory abilities. As a result, the Paraplegia group may be significantly heterogeneous with respect to motor function within the trunk. This is one possible explanation for the results of the present study which showed that the LOI groups were not significantly different from one another outside of the comparisons related to the ISNCSCI. The wide distribution of functional and spatiotemporal findings across LOI groups in the current study are supported by Kim et al (2004) who noted that subjects with paraplegia had gait speed and capacity ranges that were similarly variable to those with tetraplegia56. Although the sub-grouping of iSCI subjects on the basis of LOI may seem logical, the results of the current study and others suggest that it is an insufficient method for distinguishing subjects with distinctive walking characteristics57, 61. SOI: The ISNCSCI is a tool that allows for the classification of patients into severity of injury (SOI) groups from the onset of injury onward. There is general agreement in the literature that those classified as having an iSCI form a widely heterogeneous group with respect to clinical presentation92. Admission AIS grade has been reported as a consistent predictor of walking function in subjects with iSCI47, 55, 61. Patients classified as AIS C at one month post injury are less likely to achieve community ambulatory status and are more likely to rely on orthoses and highly stable gait aids at one year post onset than those classified as AIS D48, 55. The present study population was considerably unbalanced with respect to the

47 representation of subjects from each of the AIS categories (1.9% = AIS B, 17.3% = AIS C, 80.8% = AIS D) although the distribution is not uncommon47, 65, 122. The skewed distribution likely contributed to the differences found in the clinical measures between the SOI groups in the current study. The findings of Zorner et al (2010) support those of the current study by demonstrating that subjects of differing AIS grade have related differences in walking function 61. Interestingly, when the spatiotemporal parameters of the SOI groups in the present study were compared, no significant differences were found. When the AIS D group is examined closely, it is evident that the degree of variation within this SOI group remains high regardless of the variable examined. van Hedel and coauthors (2005) demonstrated that subtle gait impairments can be detected in subjects classified as AIS D even when clinical walking measures (in this case the 6MWT) failed to do so73. Both a 200814 and a 200991 review state that the ISNCSCI has been a very successful tool in the development of standardized terminology, but cautions that AIS classification can result in highly diverse groups and may be insensitive when used to assess for the possible benefits of an intervention14, 91. The current study findings lead to the conclusion that AIS classification is not suitable for distinguishing subject groups that are distinct with respect to their spatiotemporal gait characteristics. 5.2.2

Gait Subgroups Gait Aid: It is intuitive to assume that individuals with iSCI who use the same gait aid must share some commonalities with respect to physical presentation and gait characteristics. One of the challenges in using the gait aid as a method of subgrouping is that the type of gait aid selected by or for an individual may be dependent on many factors including: balance, upper extremity function, fear of falling, and personal or provider preference70. van Hedel et al (2008) describe cultural influence on gait aid selection and noted regional differences between Europe and the United States78. The current study population consisted of a large proportion of subjects (48.1%) who used a walker at the time of data collection. Reports of gait aid use among subjects with iSCI have shown similar distributions70. The lack of significant

48 differences between the gait aid groups with respect to the clinical measures may largely be due to the minimal data available for analysis. In contrast, the creation of subgroups on the basis of gait aid use revealed that each group had spatiotemporal characteristics that were distinguishable from one another. However, the exception was in the case of symmetry measures. When symmetry measures were compared between the gait aid groups, no significant differences were found. The similarity in symmetry values between gait aid groups may be attributable to the influence of the gait aid on an individual’s ability to generate symmetrical steps. However, the influence of a gait aid on symmetry has been shown to be minimal among subjects with other neurological conditions (e.g. stroke)123. The lack of difference in symmetry values between subject groups using different gait aids may also be due to the generally low degree of variation in symmetry values across the total study population (variance = 7-15%). Similarly to the current study, prior research has shown that among subjects with iSCI, the velocity of those who used a walker was significantly slower than the velocity of subjects who used crutches or canes54, 70. Gil-Agudo et al (2009) confirmed their hypothesis that subjects with iSCI (specifically central cord syndrome) walk slower with two crutches as compared with one, and also concluded that the balance demands of two-crutch walking were lower as demonstrated by increased single support phase duration 110. The results of these studies support the current study findings, which indicate that subjects with iSCI grouped by gait aid differ significantly from one another with respect to the spatiotemporal characteristics of their gait. Velocity: The utility of velocity as a measure of walking ability is frequently debated in the literature. Many authors have described walking speed as a measure that provides information about the overall quality of a person’s gait or their general motor function26, 72, 78, 107, 124, 125. Others caution against a heavy reliance on velocity as an outcome measure as one cannot determine why an individual walks at a particular speed from the assessment of speed alone90, 126, 127.

Within the SCI literature, the standardized collection 10mWT has been

recommended by several groups however, these groups acknowledge its limitations and suggest that the 10mWT be included as one of a set of measures78,

49 79, 91.

In 2009, van Hedel and colleagues demonstrated that among subjects with

SCI, walking speed is correlated with more global functional measures of walking105. The authors showed that walking speed, as measured by the 10mWT, can not only be used to predict walking function, but also that a minimum speed is required to achieve a particular functional level105. The velocity groups created for the purposes of comparison in the present study were formed using the velocities obtained during preferred speed walking over the GAITRite® electronic walkway. Since velocity has been correlated with TUG time and 6MWT distance78, the finding that the velocity groups differed from one another with respect to these measured was not unexpected. The influence of velocity on different spatiotemporal parameters of gait has been studied in other populations43, 69, 89, 103, 124; unfortunately, the speeds at which the subjects from these studies walked make it difficult to extrapolate to the present population whose mean preferred speed was relatively very slow. As others have noted, velocity appears to be a potentially suitable variable with which subgroups may be created56, 105. Because of its correlation with so many of the spatiotemporal variables (see Table 14), velocity has the potential to identify groups of iSCI subjects with low degrees of variation in the presentation of a particular spatiotemporal variable. The lack of differentiation in symmetry distributions between the velocity groups was again likely due to the low degree of asymmetry across the total population. Symmetry: Despite findings indicating that symmetry is a useful measure of gait performance in other neurological populations28, 86, 103, 104, 106, 111, 112, 128, neither temporal nor spatial symmetry have been widely studied among subjects with iSCI68, 74, 90. In the present study population, whether investigated with respect to spatial or temporal variables, the majority of subjects were considered symmetrical (54% temporally symmetric, 62% spatially symmetric). In general, despite grouping by symmetry values, the degree of variation within each group was relatively high and between- group comparisons revealed similar degrees of variation. Otherwise stated, neither temporal nor spatial symmetry were able to identify groups of subjects with iSCI that were unique from one another with respect to clinical or spatiotemporal measures. In the case of the temporal

50 symmetry groups where left step length variability was significantly different across the groups, the finding appears to be highly influenced by an outlier who walked at an extremely slow speed of 0.17m/s and demonstrated spatial variability of more than 40%. Variability: Measures of temporal or spatial variability have been utilized as a means of exploring the capability of the human nervous system to generate consistent locomotor output34, 36, 38, 40. A small amount (less than 5%33, 34) of step to step variability is considered to be a normal feature of human walking even when the surface and environment within which the gait is performed remains constant 33, 34. In the present study, subjects that displayed differing degrees of temporal or spatial variability during over ground walking at their preferred speed with their preferred gait aid were not significantly different from one another with respect to their clinical presentation as measured by the clinical measures listed in Table 1. It is possible that the clinical measures used are not sensitive enough to capture actual differences in subject presentation (e.g. comorbidities) or that the timing of collection was a significant confounder. One cannot dismiss the likelihood that low data completion rates of the clinical measures also negatively influenced the results. However, when this same stratification method is applied and the spatiotemporal parameters of each group are reviewed, it is clear that variability is a characteristic of gait in subjects with iSCI that has promise in its ability to distinguish unique groups of subjects from one another with respect to their gait impairments. In general, when grouped according to the degree of gait variability present, the subgroups have lower degrees of within-group variation and show less between-group overlap than subgroups created using clinical characteristics (eg. etiology) or using other gait characteristics (eg. symmetry). Information from the study of gait variability among other neurological populations and its reported usefulness in identifying individuals with impaired dynamic balance33, 35, 36, 42, 102, 112 would indicate that iSCI subjects with moderate or high spatiotemporal variability may be identified and should be monitored. The creation of variability subgroups may provide an opportunity to study the impact of particular interventions (e.g. treadmill training) on the dynamic stability of subjects

51 with low severity iSCI whose clinical outcome measures show little or no walking dysfunction35, 73. The “No Aid” Subjects: Data from the “No Aid” subjects provide an opportunity to investigate the results of the previously described sub-grouping strategies with a small subset of subjects whose spatiotemporal characteristics were not influenced by the use of a gait aid. Of the eight strategies, the sub-groupings created by dividing subjects on the basis of etiology, temporal symmetry, and spatial symmetry were least successful in distinguishing subgroups that were clinically different or that demonstrated differences in their spatiotemporal features. Once again, the limited availability of data with respect to the clinical measures likely affected the ability to create subgroups of adequate size for comparison. When each of the sub-grouping strategies is considered, there is no single method that appears to be clearly more successful than another at separating the “No Aid” subjects into subgroups that are distinct from one another. The limited amount of significant findings is likely attributable to the small number of subjects (n=11) belonging to the “No Aid” group thereby reducing the power of each comparison. 5.3 Limitations The current cross-sectional study does have several limitations. First, the data were collected by the treating PT at various, non-standardized points during the patients’ sub-acute phase. In particular, the baseline clinical measures and the spatiotemporal measurements using the GAITRite® were often collected weeks apart. At the point of care during rehabilitation, the determination of when to initiate the objective measurement of gait is usually the responsibility of the treating PT. As previously mentioned (see section 5.1), the result is a high degree of inconsistency in the timing and completion of baseline measurements. Compounding the problem is the lack of a clear and wholly accepted definition of walking within the literature and the minimum distance (10 metres) required for the completion of the most basic of outcome measures. Sturt et al (2009) showed that many patients with iSCI were only able to complete the basic clinical walking measures at a median of two months post injury47, for most patients this would occur during the rehabilitation phase. Second, the subjects were selected from an existing database of GAITRite® measures. Subjects whose data were present in the database were most likely individuals who were able

52 to walk without hands-on physical assistance and whose PT was comfortable with using the technology. Consequently, the dataset was likely biased towards subjects that had significant experience with walking and may not have been representative of the segment of the population who were just beginning to walk. Third, the number of steps or “sample size” used for the spatiotemporal variable calculations varied between subjects. All available steps collected were analyzed, but the number was not standardized between subjects. However, subjects whose data did not include at least 20 steps were excluded from this study in an effort to ensure adequate sampling 129. In the case of variability measures, the number of steps included was not as high as recommended by other authors34, 38, 43, 44 however, since there is limited evidence that variability measures have ever been collected for patients with iSCI, the sample size is acceptable for preliminary reporting. Fourth, the method of converting the symmetry ratio such that the resulting number was in all cases greater than the reference value of 1.00 (perfect symmetry) differed from the methods used by other researchers36, 68, 86, 104, 106, 112. Most commonly, a ratio in which the numerator is smaller than the denominator is converted by inverting it. It is possible that the choice of conversion method used in this paper resulted in a set of symmetry values that were nonlinear and less variable and therefore biased the results towards insignificant findings. An alternative method to the use of a ratio for symmetry evaluation is to use a symmetry differential or a symmetry index36, 68, 86, 104, 106, 112. Although no one method of symmetry calculation is considered to be superior to another, a measure which negates the direction of asymmetry may be more appropriate (e.g. asymmetry = [absolute(R-L)/0.5(R+L)] X100%)106 in cases where the neurological lesion does not have clear sidedness (as in iSCI), Fifth, much of the spatiotemporal data analysis involved the comparison of values measured from either the right or left limb. The analysis may have been more accurate if the data from each subject’s strong or weak limb were compared. This was not done in the current study because the LEMS were collected at admission and information as to which limb was strongest at the time of the spatiotemporal data collection was unknown. Sixth, an analysis of the differences between groups formed on the basis of time since onset of injury was not undertaken. It is possible that such an analysis, even of cross-sectional data, could reveal important information about the influence of time on the gait characteristics of subjects with sub-acute iSCI.

53 Lastly, the available sample sizes for many of the sub-group comparisons may have led to Type II errors. For each comparison made, the null hypothesis was that the distribution of the variable was the same across the sub-groups. The repeated erroneous acceptance of this null hypothesis would result in an interpretation of the results to mean that there were no significant differences between the groups when a difference did actually exist. A secondary analysis such as the present study does not allow for the predetermination of appropriate sample sizes, however it is clear that the likelihood of this type of error could be greatly reduced by ensuring an adequate sample size for each sub-group held up for comparison. In addition, normalization of the data through log or power transformation may have reduced the risk of Type II errors in this data set. 6.0 Overall Conclusions 6.1 Walking in iSCI: Descriptors and Measures The population of subjects included in the present study has been described on the basis of subject characteristics, clinical walking measures, and spatiotemporal parameters of gait. As many authors have noted, subjects with iSCI are a highly heterogeneous group15, 68, 92 and the current study supports these findings. The description of the walking ability of subjects with iSCI is commonly achieved through the use of clinical walking measures and the current literature supports this for both clinical and research practice69, 78, 79, 81, 91, 92, 94, 108. Unfortunately, the valid and reliable clinical measures available for use with iSCI subjects are largely categorical or descriptive in nature. As a result these measures are useful for the description of a subject’s functional walking abilities and may be adequately sensitive to provide information about change in status91 but they lack an ability to direct intervention selection 90, 126. The inclusion of spatiotemporal measurement is not common practice either in SCI research or clinical practice97, however the additional information that these measures provide is clearly of value59, 73, 97, 130. The collection of spatiotemporal details about the walking patterns adopted by subjects with sub-acute iSCI may allow for clinicians and researchers to develop methods of identifying patients or subjects who would most benefit from a particular rehabilitation intervention68 or who are at risk of certain secondary complications (e.g. arthropathy, falls) as has been achieved for other neurological populations (e.g. stroke, Parkinson’s Disease, Multiple Sclerosis, Alzheimer’s Disease)36, 42, 45, 102, 107, 112, 128, 131. The collection of spatiotemporal information moves the field of gait analysis in iSCI further towards a state of being directive or prescriptive87, 97, 111, 126 and answers the call for measures that are reflective of impairments in dynamic postural control35, 65, 81.

54 6.2 Sub-grouping of subjects with iSCI The findings of the current analysis indicate that the sub-grouping of subjects with sub-acute iSCI on the basis of etiology, LOI, and SOI is inadequate to distinguish groups of subjects that are significantly different from one another with respect to their gait impairments. Alternatively, the use of spatiotemporal gait characteristics for the purposes of sub-grouping holds promise. The ability to characterize the iSCI population into clinically meaningful homogenous sub-groups has the potential to diminish the inconclusive findings that now prevail in interventional SCI research14. The findings presented herein indicate that the spatiotemporal variables that warrant further study as potential treatment effect modifiers are velocity and variability. For example, subjects with iSCI could be prospectively stratified into two temporal variability groups (low step time variability ≤5% and high step time variability >5%) using temporal data. Following a period of treadmill training with concurrent rhythmic auditory stimulation (set at a rate =100% of preferred cadence) the spatiotemporal measures would be repeated to determine if the treatment had an effect on temporal variability. 6.3 Recommendations from current study The present study confirms the need to standardize not only which measures of walking are performed, but also that a systematic timeline for their collection is agreed upon so that betweensubject, between-subject group, and between-study comparisons can be made. Most commonly, clinicians rely on measurement collection to be triggered by either a change in the subject’s location in the healthcare system or their own individual decision-making. Unfortunately, admission and discharge dates are highly variable and influenced by a multitude of factors (e.g. health system pressures and psychosocial factors). Although the ability to standardize outcome measurement was not achievable in the current secondary data analysis, it is recommended that future measurement of walking be defined by time since onset rather than point of care. The comprehensive assessment of a patient with iSCI must include a variety of measures appropriate to his or her stage of recovery (see Figure 14). These stages, as they relate to walking and how it changes over time, include: Pre-Walking, Early Walking, Walking, and Consistent Walking Features/Functions. Descriptors of the SCI with respect to its cause, severity, and neurological level need to continue to be identified at SCI onset. Because severity and level of injury can change, these should be re-assessed at regular intervals. From the point of SCI onset, it is recommended that the Spinal Cord Independence Measure (SCIM) be collected in place of the

55 FIM as it has been shown to have greater specificity in the measurement of functional independence in the SCI population91, 94. As the LEMS has been identified as a predictor of the achievement of walking53 and has the potential to identify subjects who are most likely to have issues with gait symmetry, it is recommended that the LEMS and a LEMS symmetry ratio be collected at regular intervals throughout the sub-acute phase. A LEMS symmetry ratio of ≥1.40 represents an individual who has a score differential of 10 points. Based on the current study sample, 1.40 was selected as a threshold for identifying subjects with significant motor function asymmetry (e.g. Right LEMS=15, Left LEMS=25) and who would be expected to demonstrate considerable gait asymmetry. Information about gait velocity can be obtained using a system such as the GAITRite® and as a result, the 10mWT becomes a redundant measure if spatiotemporal measures are to be collected as recommended. It is recommended that measures such as the TUG and spatiotemporal parameters be initiated in the Pre-Walking stage so that they may aid in the identification of walking onset. With the appropriate safety precautions in place (such as a safety harness), subjects could walk without gait aids during the collection of spatiotemporal data thus removing aid use as a confounding factor. The measurement of the 6MWT distance is recommended to be completed from the Walking stage onward at the point in time that the subject demonstrates an ability to walk continuously for a distance greater than 30m (one length of the recommended track for the 6MWT84). It is clear that some record of the assistive device(s) used by the subject for walking is necessary, however because the selection of an aid may be influenced by a number of factors70, 78 this type of measure may be more suited to the later stages of walking recovery. Since the intended purpose of the WISCI was that it be used to define impairment through walking capacity testing60, the ADS may be more suited to functioning as an objective means of noting assistive device use. As a result of the prior recommendation to collect the SCIM, the WMS becomes redundant and has therefore been removed from the list of recommended measures to assist in maintaining clinical feasibility. The collection of spatiotemporal parameters for individuals with iSCI is recommended both on the basis of the limitations of clinical measures and on the potential that spatiotemporal data have to influence clinical intervention. For example, spatiotemporal data which indicates that a patient has a high degree of spatial variability could direct a physiotherapist towards an intervention such as a robotic gait trainer (e.g. Lokomat) which allows for repetitive practice of consistent stepping

56 patterns with constrained spatial variability76, 77. It is recommended that the collection of spatiotemporal measures include: phase durations, temporal and spatial variability, and temporal and spatial symmetry (in those cases where the LEMS symmetry ratio is ≥1.40 as described above). Figure 14: Model of Walking Measurement Recommendations – the model depicts each measure plotted on a time continuum referenced from SCI Onset (time 0) and related to the phases of walking recovery

The frequent reliance on etiology or injury severity to act as variables upon which to base inclusion/exclusion criteria or sub-grouping has been clearly challenged. Although the findings of the present study only begin to point to alternative choices, they support the notion that useful measures must not only act to characterize a patient but also provide the opportunity to direct the selection of treatment options126, 127.

57 6.3.1

Summary of Recommendations for Measuring Walking in iSCI During Rehabilitation TIMING OF MEASUREMENT:



Use time of SCI onset as time zero from which to base time frame of measurement



Describe SCI on basis of etiology at time of SCI onset and on basis of severity and neurological level of injury through sub-acute and chronic phases



Begin collecting TUG and spatiotemporal parameters in Pre-Walking Phase (before subject is able to complete distance of 10m)



Collect 6MWT in Walking Phase (once subject is able to walk distance >30m)

RECOMMENDED MEASURES:



Measure LEMS and calculate LEMS Symmetry Ratio at regular intervals through the sub-acute phase



Use SCIM as a more sensitive measure of functional independence (FIM and WMS redundant)



Record assistive device use throughout sub-acute and chronic phase with ADS



Spatiotemporal parameters collected should include: ▫ Phase durations ▫ Temporal and spatial variability ▫ Temporal and spatial symmetry (for those with LEMS Symmetry Ratio >1.40)

6.4 Future directions The study of walking in subjects with iSCI will no doubt continue to gain momentum as cellular science approaches major discoveries in spinal cord recovery and repair. Future research may investigate the spatiotemporal characteristics of iSCI gait longitudinally such that determinations can be made as to how these features change over time. As eluded to by Patrick (2003) and Baker (2006), spatiotemporal measures may be more sensitive to change than traditional clinical measures97, 126. If standardized spatiotemporal data can be captured in a clinical database, a cross-sectional secondary analysis across multiple time points could provide information as to how the gait of subjects post-iSCI changes over time. Given that most of the data described in this study were not normally distributed, future studies with larger cohorts should take into consideration the possibility that spatiotemporal data collected from the sub-acute iSCI population may have gamma or lognormal distributions and therefore may necessitate regression modeling analyses.

58 The paucity of information available about both the spatial and temporal variability of post-iSCI gait highlights the need for simple descriptive studies to be conducted. The measurement of variability among iSCI subjects walking at a variety of velocities would provide appropriate normative data for comparison. Related directions for future research include: 

the study of the relationship between variability and fall risk



the examination of whether gait variability increases during long duration walking in the sub-acute iSCI population



the determination of whether subjects with higher degrees of spatial variability in the subacute phase are less likely to achieve un-aided walking than those with higher degrees of temporal variability.

Despite significant progress in the ability to describe the gait of individuals with iSCI, explanations as to why subjects with iSCI walk the way they do and how clinicians can modify or influence these patterns in the sub-acute phase are still needed. The identification of interventions which are most beneficial to patients with particular gait characteristics would greatly improve rehabilitation efficiency.

7.0 References 1.

Ditunno P, Patrick M, Stineman M, Ditunno J. Who wants to walk? Preferences for recovery after SCI: a longitudinal and cross-sectional study. Spinal Cord 2008;46:500-6.

2.

Hesse S, Werner C. Connecting research to the needs of patients and clinicians. Brain Research Bulletin 2009;78:26-34.

3.

Kirshblum S, Priebe M, Ho C, Scelza W, Chiodo A, Wuermser L. Spinal Cord Injury Medicine. 3. Rehabilitation Phase After Acute Spinal Cord Injury. Archives of Physical Medicine and Rehabilitation 2007;88(3 Suppl. 1):S62-70.

4.

Scivoletto G, Ivanenko Y, Morganti B, Grasso R, Zago M, Lacquniti F et al. Plasticity of Spinal Centers in Spinal Cord Injury Patients: New Concepts for Gait Evaluation and Training. Neurorehabilitation and Neural Repair 2007;21:358-65.

5.

Pirouzmand F. Epidemiological trends of spine and spinal cord injuries in the largest Canadian adult trauma center from 1986 to 2006. Journal of Neurosurgery: Spine 2010;12:131-40.

6.

Pickett W, Simpson K, Walker J, Brison R. Traumatic Spinal Cord Injury in Ontario, Canada. Journal of Trauma 2003;55(6):1070-6.

7.

Guilcher S, Munce S, Couris C, Fung K, Craven B, Verrier M et al. Health care utilization in non-traumatic and traumatic spinal cord injury: a population-based study. Spinal Cord 2010;48:45-50.

8.

Sekhon L, Fehlings M. Epidemiology, Demographics, and Pathophysiology of Acute Spinal Cord Injury. Spine 2001;26(24S):S2-12.

9.

Spinal Cord Injury Facts and Figures at a Glance. National Spinal Cord Injury Statistical Centre; 2010.

10.

Institute RH. SCI Facts 2010 [cited 2011 July 17, 2011]. Available from: URL: www.rickhansenregistry.org.

11.

Association ASI. International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) [cited 2011 August 20, 2011]. Available from: URL: www.asiaspinalinjury.org.

12.

Barbeau H, Nadeau S, Garneau C. Physical Determinants, Emerging Concepts, and Training Approaches in Gait of Individuals with Spinal Cord Injury. Journal of Neurotrauma 2006;23(3/4):571-85.

13.

Foundation HaS. Stroke Statistics 2011 [cited 2011 June 26, 2011]. Available from: URL: www.heartandstroke.on.ca.

14.

Mehrholz J, Kugler J, Pohl M. Locomotor training for walking after spinal cord injury. Cochrane Database of Systematic Reviews 2008(4):CD006676. 59

60 15.

Bromley I. Tetraplegia and Paraplegia: A Guide for Physiotherapists. 6th ed. Toronto: Churchill Livingston Elsevier; 2006.

16.

Leonard C. The Neuroscience of Human Movement. New York: Mosby; 1998.

17.

Al-Obaidi S, Wall J, Al-Yaqoub A, Al-Ghanim M. Basic gait parameters: A comparison of reference data for normal subjects 20 to 29 years of age from Kuwait and Scandinavia. Journal of rehabilitation research and development 2003;40(4):361-6.

18.

Sadeghi H, Allard P, Prince F, Labelle H. Symmetry and limb dominance in able-bodied gait: a review. Gait and Posture 2000;12:34-45.

19.

Kuo A, Donelan J. Dynamic Principles of Gait and Their Clinical Implications. Physical Therapy 2010;90(2):157-74.

20.

Perry J. Gait. 4th ed. Los Angeles; 2001.

21.

Kandel E, Schwartz J, Jessell T, editors. Principles of Neural Science. 4th ed. London: McGraw Hill; 2000.

22.

Shumway-Cook A, Woolacott M. Motor Control Theory and Practical Applications. Williams and Wilkins; 1995.

23.

Ivanenko Y, Poppele R, Lacquanti. Distributed neural networks for controlling human locomotion. Lessons from normal and SCI subjects. Brain Research Bulletin 2009;78:13-21.

24.

Norkin C, Levangie P, editors. Joint Structure and Function: A Comprehensive Analysis. 2nd ed. Philadelphia: F.A. Davis Company; 1992.

25.

Oberg T, Karsznia A, Oberg K. Basic gait parameters: Reference data for normal subjects, 10-79 years of age. Journal of Rehabilitation Research 1993;30(2):210-23.

26.

Bohannon R. Comfortable and maximum walking speed of adults aged 20-79 years: reference values and determinants. Age and Ageing 1997;26:15-9.

27.

GAITRite Electronic Walkway Technical Reference. Peekskill, NY: CIR Systems Inc.; 2010. p 31.

28.

Kim C, Eng J. Symmetry in vertical ground reaction force is accompanied by symmetry in temporal but not distance variables of gait in persons with stroke. Gait and Posture 2003;18:23-8.

29.

Goble D, Marino G, Potvin J. The influence of horizontal velocity on interlimb symmetry in normal walking. Human Movement Science 2003;22:271-83.

30.

Stolze H, Friedrich H, Steinauer K, Vieregge P. Stride Parameters in Healthy Young and Old Women - Measurement Variability on a Simple Walkway. Experimental Aging and Research 2000;26:159-68.

61 31.

Tura A, Raggi M, Rocchi L, Cutti A, Chiari L. Gait symmetry and regularity in transfemoral amputees assessed by trunk accelerations. Journal of NeuroEngineering and Rehabilitation 2010;7(4).

32.

Reisman D, Block H, Bastian A. Interlimb Coordination During Locomotion: What Can Be Adapted and Stored. Journal of Neurophysiology 2005;94:2403-15.

33.

Hausdorff J. Gait variability: methods, modeling and meaning. Journal of NeuroEngineering and Rehabilitation 2005;2(19).

34.

Danion F, Varraine E, Bonnard M, Pailhous J. Stride variability in human gait: the effect of stride frequency and stride length. Gait and Posture 2003;18:69-77.

35.

Niechwiej-Szwedo E, Inness E, Howe J, Jaglal S, McIroy W, Verrier M. Changes in gait variability during different challenges to mobility in patients with traumatic brain injury. Gait and Posture 2007;25:70-7.

36.

Balasubramanian C, Neptune R, Kautz S. Variability in spatiotemporal step characteristics and its relationship to walking performance post-stroke. Gait and Posture 2009;29:408-14.

37.

Li L, Haddad J, Hamill J. Stability and variability may respond differently to changes in walking speed. Human Movement Science 2005;24:257-67.

38.

Grabiner P, Biswas T, Grabiner M. Age-Related Changes in Spatial and Temporal Gait Variables. Archives of Physical Medicine and Rehabilitation 2001;82:31-5.

39.

Owings T, Grabiner M. Variability of step kinematics in young and older adults. Gait and Posture 2004;20:26-9.

40.

Beauchet O, Allali G, Annveiler C, Bridenbaugh A, Assal F, Kressig R et al. Gait Variability among Healthy Adults: Low and High Stride-to-Stride Variability Are Both a Reflection of Gait Stability. Gerontology 2009;55:702-6.

41.

Maki B. Gait Changes in Older Adults: Predictors of Falls or Indicators of Fear? Journal of the American Geriatrics Society 1997;54:313-20.

42.

Brach J, Berlin J, VanSweringen J, Newman A, Studenski S. Too much or too little step width variability is associated with a fall history in older persons who walk at or near normal gait speed. Journal of NeuroEngineering and Rehabilitation 2005;2(21).

43.

Beauchet O, Annweiler C, Lecordoch Y, Allali G, Dubost V, Herrmann F et al. Walking speedrelated changes in stride time variability: effects of decreased speed. Journal of NeuroEngineering and Rehabilitation 2009;6(32).

44.

Dubost V; Kressig RG, R; Herrmann, FR; Aminian, K; Najafi, B; Beauchet, O. Relationships between dual-task related changes in stride velocity and stride time variability in healthy older adults. Human Movement Science 2006;25:372-82.

62 45.

Hausdorff J, Rios D, Edelberg H. Gait Variability and Fall Risk in Community-Living Older Adults: A 1-Year Prospective Study. Archives of Physical Medicine and Rehabilitation 2001;82:1050-6.

46.

Wirz M, van Hedel H, Rupp R, Curt A. Muscle Force and Gait Performance: Relationships After Spinal Cord Injury. Archives of Physical Medicine and Rehabilitation 2006;87:1218-22.

47.

Sturt R, Holland A, New P. Walking ability at discharge from inpatient rehabilitation in a cohort of non-traumatic spinal cord injury patients. Spinal Cord 2009.

48.

Dobkin B, Barbeau H, Deforge D, Ditunno J, Elashoff R, Apple D et al. The evolution of walking-related outcomes over the first 12 weeks of rehabilitation for incomplete traumatic spinal cord injury: the multicenter randomized Spinal Cord Injury Locomotor Trial. Neurorehabilitation and Neural Repair 2007;21:25-35.

49.

Waters R, Adkins R, Yakura J, Sie I. Motor and Sensory Recovery Following Incomplete Paraplegia. Archives of Physical Medicine and Rehabilitation 1994;75:67-72.

50.

Waters R, Adkins R, Yakura J, Sie I. Motor and Sensory Recovery Following Incomplete Tetraplegia. Archives of Physical Medicine and Rehabilitation 1994;75:306-11.

51.

Burns S, Golding D, Rolle W, Graziani V, Ditunno J. Recovery of Ambulation in MotorIncomplete Tetraplegia. Archives of Physical Medicine and Rehabilitation 1997;78:1169-72.

52.

Lapointe R, Lajoie Y, Serresse O, Barbeau H. Functional community ambulation requirements in incomplete spinal cord injured subjects. Spinal Cord 2001;39:327-35.

53.

Waters R, Adkins R, Yakura J, Vigil D. Prediction of Ambulatory Performance Based on Motor Scores Derived from Standards of the American Spinal Injury Association. Archives of Physical Medicine and Rehabilitation 1994;75:756-60.

54.

Waters R, Yakura J, Adkins R, Barnes G. Determinants of Gait Performance. Archives of Physical Medicine and Rehabilitation 1989;70:811-8.

55.

Kay E, Deutsch A, Wuermser L. Predicting Walking at Discharge From Inpatient Rehabilitation After a Traumatic Spinal Cord Injury. Archives of Physical Medicine and Rehabilitation 2007;88:745-50.

56.

Kim C, Eng J, Whittaker M. Level walking and ambulatory capacity in persons with incomplete spinal cord injury relationship with muscle strength. Spinal Cord 2004;42:15662.

57.

Crozier K, Cheng L, Graziani V, Zorn G, Herbison G, Ditunno J. Spinal cord injury: prognosis for ambulation based on quadriceps recovery. Paraplegia 1992;30:762-7.

58.

Cosar S, Yemisci O, Oztop P, Cetin N, Sarifakiouglu B, Yalbuzdag S et al. Demographic characteristics after traumatic and non-traumatic spinal cord injury: a retrospective comparison study. Spinal Cord 2010;48:862-6.

63 59.

Pepin A, Norman K, Barbeau H. Treadmill walking in incomplete spinal-cord-injured subjects: 1. Adaptation to changes in speed. Spinal Cord 2003;41:257-70.

60.

Ditunno J, Burns A, Marino R. Neurological and functional capacity outcome measures: Essential to spinal cord injury clinical trials. journal of rehabilitation research and development 2005;42(3):35-42.

61.

Zorner B, Blanckenhorn W, Dietz V, Group E-SS, Curt A. Clinical Algorithm for Improved Prediction of Ambulation and Patient Stratification after Incomplete Spinal Cord Injury. Journal of Neurotrauma 2010;27:241-52.

62.

Waters R, Adkins R, Yakura J, Sie I. Functional and Neurologic Recovery Following Acute SCI. Journal of Spinal Cord Medicine 1998;21:195-9.

63.

Marino R, Ditunno J, Donovan W, Maynard F. Neurologic Recovery After Traumatic Spinal Cord Injury: Data From the Model Spinal Cord Injury Systems. Archives of Physical Medicine and Rehabilitation 1999;80:1391-6.

64.

Crozier K, Graziani V, Ditunno J, Herbison G. Spinal Cord Injury: Prognosis for Ambulation Based on Sensory Examination in Patients Who Are Initially Motor Complete. Archives of Physical Medicine and Rehabilitation 1991;72:119-21.

65.

Scivoletto G, Romanelli A, Mariotti A, Marinucci D, Tamburella F, Mammone A et al. Clinical Factors That Affect Walking Level and Performance in Chronic Spinal Cord Lesion Patients. Spine 2008;33:259-64.

66.

Dietz V, Harkema S. Locomotor activity in spinal cord-injured persons. Journal of Applied Physiology 2004;96:1954-60.

67.

Lam T, Eng J, Wolfe D, Hsieh J, Whittaker M, Team SR. A Systematic Review of the Efficacy of Gait Rehabilitation Strategies for Spinal Cord Injuries. Topics in Spinal Cord Injury Rehabilitation 2007;13(1):32-57.

68.

Field-Fote E, Lindley S, Sherman A. Locomotor Training Approaches for Individuals with Spinal Cord Injury: A Preliminary Report of Walking-related Outcomes. Journal of Neurological Physical Therapy 2005;29(3):127-37.

69.

van Hedel H, Dietz V, Curt A. Assessment of Walking Speed and Distance in Subjects with an Incomplete Spinal Cord Injury. Neurorehabilitation and Neural Repair 2007;21(4):295-301.

70.

Melis E, Torres-Moreno R, Barbeau H, Lemaire E. Analysis of assisted-gait characteristics in persons with incomplete spinal cord injury. Spinal Cord 1999;37:430-9.

71.

Pepin A, Ladouceur M, Barbeau H. Treadmill walking in incomplete spinal-cord-injured subjects: 2. Factors limiting the maximal speed. Spinal Cord 2003;41:271-9.

72.

Barbeau H, Elashoff R, Deforge D, Ditunno J, Saulino M, Dobkin B. Comparison of Speeds Used for the 15.2-Meter and 6-Minute Walks Over the Year After an Incomplete Spinal Cord Injury: The SCILT Trial. Neurorehabilitation and Neural Repair 2007;21(4):302-6.

64 73.

van Hedel H, Wirth B, Dietz V. Limits of locomotor ability in subjects with a spinal cord injury. Spinal Cord 2005;43:593-603.

74.

Visintin M, Barbeau H. The effects of parallel bars, body weight support and speed on the modulation of the locomotor pattern of spastic paretic gait. A preliminary communication. Paraplegia 1994;32:540-53.

75.

Amatachaya S, Keawsutthi M, Amatachaya P, Manimmanakorn N. Effects of external cues on gait performance in independent ambulatory incomplete spinal cord injury patients. Spinal Cord 2009;47:668-73.

76.

Duschau-Wicke A, Caprez A, Reiner R. Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training. Journal of NeuroEngineering and Rehabilitation 2010;7(43).

77.

Emken J, Harkema S, Beres-Jones J, Ferreira C, Reinkensmeyer D. Feasibility of Manual Teach-and-Replay and Continuous Impedance Shaping for Robotic Locomotor Training Following Spinal Cord Injury. IEEE Transactions on Biomedical Engineering 2008;55(1):32234.

78.

van Hedel H, Wirz M, Dietz V. Standardized assessment of walking capacity after spinal cord injury: the European network approach. Neurological Research 2008;30:61-73.

79.

Jackson A, Carnel C, Ditunno J, Schmidt Read M, Boninger J, Schmeler M et al. Outcome Measures for Gait and Ambulation in the Spinal Cord Injury Population. Journal of Spinal Cord Medicine 2008;31:487-99.

80.

Coutts F. Gait analysis in the therapeutic environment. Manual Therapy 1999;4(1):2-10.

81.

Lam T, Noonan V, Eng J, Team SR. A systematic review of functional ambulation outcome measures in spinal cord injury. Spinal Cord 2008;46:246-54.

82.

Scivoletto G, Tamburella F, Laurenza L, Foti C, Ditunno J, Molinari M. Validity and reliability of the 10-m walk test and the 6-min walk test in spinal cord injury patients. Spinal Cord 2011;49:736-40.

83.

van Hedel H, Wirz M, Dietz V. Assessing Walking Ability in Subjects with Spinal Cord Injury: Validity and Reliability of 3 Walking Tests. Archives of Physical Medicine and Rehabilitation 2005;86:190-6.

84.

Society AT. ATS Statement: Guidelines for the Six-Minute Walk Test. American Journal of Respiratory Critical Care Medicine 2002;166:111-7.

85.

Liu J, Drutz C, Kumar R, McVicar L, Weinberger R, Brooks D et al. Use of the Six-Minute Walk Test Poststroke: Is There a Practice Effect? Archives of Physical Medicine and Rehabilitation 2008;89:1686-92.

65 86.

Sibley K, Tang A, Patterson K, Brooks D, McIlroy W. Changes in spatiotemporal gait variables over time during a test of functional capacity after stroke. Journal of NeuroEngineering and Rehabilitation 2009;6(27).

87.

Givon U, Zeilig G, Achiron A. Gait analysis in multiple sclerosis: Characterization of temporal-spatial parameters using GAITRite functional ambulation system. Gait and Posture 2009;29:138-42.

88.

Posiadlo D, Richardson S. The Timed "Up & Go": A Test of Basic Functional Mobility for Frail Elderly Persons. Journal of the American Geriatrics Society 1991;39:142-8.

89.

Tyson S, Connell L. The psychometric properties and clinical utility of measures of walking and mobility in neurological conditions: a systematic review. Clinical Rehabilitation 2009;23:1018-33.

90.

Field-Fote E, Fluet G, Schafer S, Schneider E, Smith R, Downey P et al. The Spinal Cord Injury Functional Ambulation Inventory (SCI-FAI). Journal of Rehabilitation Medicine 2001;33:177-81.

91.

Alexander M, Anderson K, Biering-Sorensen F, Blight A, Brannon R, Bryce T et al. Outcome measures in spinal cord injury: recent assessments and recommendations for future directions. Spinal Cord 2009;47:582-91.

92.

Dawson J, Shamley D, Jamous M. A structured review of outcome measures used for the assessment of rehabilitation interventions for spinal cord injury. Spinal Cord 2008;46:76880.

93.

Marino R, Scivoletto G, Patrick M, Tamburella F, Read M, Burns A et al. Walking Index for Spinal Cord Injury Version 2 (WISCI-II) with Repeatability of the 10-m Walk Time Inter- and Intrarater Reliabilities. American Journal of Physical Medicine & Rehabilitation 2010;89:7-15.

94.

Anderson K, Aito S, Atkins M, Biering-Sorensen F, Charlifue S, Curt A et al. Functional Recovery Measures for Spinal Cord Injury: An Evidence-Based Review for Clinical Practice and Research. Journal of Spinal Cord Medicine 2008;31(2):133-44.

95.

McDonough A, Batavia M, Chen F, Kwon S, Ziai J. The Validity and Reliability of the GAITRite System's Measurements: A Preliminary Evaluation. Archives of Physical Medicine and Rehabilitation 2001;82:419-25.

96.

Menz H, Latt M, Tiedemann A, Kwan M, Lord S. Reliability of the GAITRite walkway system for the quantification of temporo-spatial parameters of gait in young and older people. Gait and Posture 2004;20:20-5.

97.

Patrick J. The Case for gait analysis as part of the management of incomplete spinal cord injury. Spinal Cord 2003;41:479-82.

98.

Cutlip R, Mancinelli C, Huber F, DiPasquale J. Evaluation of an instrumented walkway for measurement of the kinematic parameters of gait. Gait and Posture 2000;12:134-8.

66 99.

Bilney B, Morris M, Webster K. Concurrent related validity of the GAITRite walkway system for quantification of the spatial and temporal parameters of gait. Gait and Posture 2003;17:68-74.

100.

Webster K, Wittwer J, Feller J. Validity of the GAITRite walkway system for the management of averaged and individual step parameters of gait. Gait and Posture 2005;22:317-21.

101.

van Uden C, Besser M. Test-retest reliability of temporal and spatial gait characteristics measured with an instrumented walkway system (GAITRite). BMC Musculoskeletal Disorders 2004;5(13).

102.

Nadkarni N, Mawji E, McIlroy W, Black S. Spatial and temporal gait parameters in Alzheimer's disease and aging. Gait and Posture 2009;30:452-4.

103.

Balasubramanian C, Bowden M, Neptune R, Kautz S. Relationship Between Step Length Asymmetry and Walking Performance in Subjects With Chronic Hemiparesis. Archives of Physical Medicine and Rehabilitation 2007;88.

104.

Patterson K, Parafianowicz I, Danells C, Closson V, Verrier M, Staines W et al. Gait Asymmetry in Community-Ambulating Stroke Survivors. Archives of Physical Medicine and Rehabilitation 2008;89:304-10.

105.

van Hedel H. Gait Speed in Relation to Categories of Functional Ambulation After Spinal Cord Injury. Neurorehabilitation and Neural Repair 2009;23(4):343-50.

106.

Patterson K, Gage W, Brooks D, Black S, McIlroy W. Evaluation of gait symmetry after stroke: A comparison of current methods and recommendations for standardization. Gait and Posture 2010;31:241-6.

107.

Roth E, Merbitz C, Mroczek K, Dugan S, Suh W. Hemiplegic Gait: Relationships Between Walking Speed and Other Temporal Parameters. American Journal of Physical Medicine & Rehabilitation 1997;76(2):128-33.

108.

van Hedel H, Dietz V, Group EMSoHSCIS. Walking During Daily Life Can Be Validly and Responsively Assessed in Subjects With a Spinal Cord Injury. Neurorehabilitation and Neural Repair 2009;23(2):117-24.

109.

England S, Granata K. The influence of gait speed in local dynamic stability of walking. Gait and Posture 2007;25:172-8.

110.

Gil-Agudo A, Perez-Rizo E, Ama-Espinosa A, Crespo-Ruiz B, Perez-Nombela S, SanchezRamos A. Comparative biomechanical gait analysis of patients with central cord syndrome walking with one crutch and two crutches. Clinical Biomechanics 2009;24:551-7.

111.

Dewar M, Judge G. Temporal asymmetry as a gait quality indicator. Medical and Biological Engineering and Computing 1980;18:689-93.

112.

Prosser L, Lauer R, VanSant A, Barbe M, Lee S. Variability and symmetry of gait in early walkers with and without bilateral cerebral palsy. Gait and Posture 2010;31:522-6.

67 113.

Callisaya M, Blizzard L, McGinley J, Schmidt M, Srikanth V. Sensorimotor Factors Affecting Gait Variability in Older People - A Population-Based Study. Journal of Gerontology 2010;65A(4):386-92.

114.

Hausdorff J. Stride variability: beyond length and frequency. Gait and Posture 2004;20:304.

115.

Kent P, Keating J, Leboeuf-Yde C. Research methods for subgrouping low back pain. BMC Medical Research Methodology 2010;10(62).

116.

Rothwell P. Subgroup analysis in randomised controlled trials: importance, indications, and interpretation. The Lancet 2005;365:176-86.

117.

Hancock M, Herbert R, Maher C. A Guide to Interpretation of Studies Investigating Subgroups of Responders to Physical Therapy Interventions. Physical Therapy 2009;89(7):698-704.

118.

Gupta A, Taly A, Srivastava A, Murali T. Non-traumatic spinal cord lesions: epidemiology, complications, neurological and functional outcome of rehabilitation. Spinal Cord 2009;47:307-11.

119.

Ones K, Yilmz E, Beydogan A, Gultekin O, Caglar N. Comparison of functional results in non-traumatic and traumatic spinal cord injury. Disability and Rehabilitation 2007;29(15):1185-91.

120.

Wyndaele M, Wyndaele J-J. Incidence, prevalence and epidemiology of spinal cord injury: what learns a worldwide literature survey? Spinal Cord 2006;44:523-9.

121.

Dryden D, Saunders L, Rowe B, LA M, Yiannakoulias N, Svenson L et al. The Epidemiology of Traumatic Spinal Cord Injury in Alberta, Canada. Canadian Journal of Neurological Sciences 2003;30:113-21.

122.

Pickett G, Campos-Benitez M, Keller J, Duggal N. Epidemiology of Traumatic Spinal Cord Injury in Canada. Spine 2006;31(7):799-805.

123.

Tyson S. Hemiplegic gait symmetry and walking aids. Physiotherapy Theory and Practice 1994;10:153-9.

124.

Andriacchi T, Ogle J, Galante J. Walking Speed as a Basis of Normal and Abnormal Gait Measurements. Journal of Biomechanics 1977;10:261-8.

125.

Graham J, Ostir G, Fisher S, Ottenbacher K. Assessing walking speed in clinical research: a systematic review. Journal of Evaluation in Clinical Practice 2008;14:552-62.

126.

Baker R. Gait analysis methods in rehabilitation. Journal of NeuroEngineering and Rehabilitation 2006;3(4).

127.

Olney S, Griffin M, McBride I. Temporal, Kinematic, and Kinetic Variables Related to Gait Speed in Subjects with Hemiplegia: A Regression Approach. Physical Therapy 1994;74(9):872-85.

68 128.

Yogev G, Plotnik M, Peretz C, Giladi N, Hausdorff J. Gait asymmetry in patients with Parkinson's disease and elderly fallers: when does the bilateral coordination of gait require attention? Experimental Brain Research 2007;177:336-46.

129.

Kressig R, Beauchet O. Guidelines for clinical applications of spatio-temporal gait analysis in older adults. Aging Clinical and Experimental Research 2006;18(2):174-6.

130.

Chang H, Chuang T, Lee S, Liao S, Lee H, Shih Y et al. Temporal differences in relative phasing of gait initiation and first step length in patients with cervical and lumbosacral spinal cord injuries. Spinal Cord 2004;42:281-9.

131.

Plotnik M, Giladi N, Hausdorff J. Bilateral coordination of gait and Parkinson's disease: the effects of dual tasking. Journal of Neurosurgery and Psychiatry 2009;80:347-50.

8.0 Appendices 8.1 Appendix A: Results for Total Study Population 8.1.1 Clinical Measures

69

8.1.2

Spatiotemporal Correlations

Table 14: Correlations between Spatiotemporal Parameters for Total Study Population PARAMETER

Cadence

Stance %GC

Swing %GC

SS %GC

DS %GC

Temp. Stance Symm

Temp. Swing Symm

Total Temp. Symm

Spatial Symm

Temp. Variability %CV

Spatial Var %CV

L

R

L

R

L

R

L

R

L

R

L

R

-0.615**

-0.892**

0.616**

0.776**

0.768**

0.624**

-0.849**

-0.835**

0.001

-.232

-0.163

-0.212

-0.665**

-0.658**

-0.592**

-0.649**

-0.552**

-0.755**

0.551**

0.755**

0.747**

0.554**

-0.781**

-0.780

-0.018

-0.270

-0.183

-0.149

-0.554**

-0.605**

-0.439**

-0.468

Lt Stance %GC

-1.000

-0.391**

-0.386**

-.988**

0.734**

0.725**

0.126

0.525**

0.384**

0.538**

0.471**

Rt Stance %GC

-0.391**

-1.000**

-0.996**

-0.404**

0.883**

0.887**

Lt Swing %GC

0.385**

0.989**

-0.734**

-0.725**

0.295*

Rt Swing %GC

0.996**

0.404**

-0.883**

-0.887**

-0.162

Left SS %GC

-0.882**

-0.889**

-0.162

-0.350*

-0.272

Right SS %GC

-0.736**

-0.723**

0.312*

0.075

Velocity Cadence

0.869**

-0.048 0.342*

0.185

0.499**

0.523**

0.421**

0.468**

-0.126

-0.527**

-0.384**

-0.540**

-0.470**

-0.185

-0.499**

-0.523**

-0.421**

-0.468**

-0.200

-0.488**

-0.504**

-0.405**

-0.457**

0.442

-0.130

-0.514**

-0.387**

-0.562**

-0.465**

Left DS %GC

0.010

0.262

0.180

0.209

0.614**

0.534**

0.576**

0.588**

Right DS %GC

0.034

0.282*

0.202

0.239

0.589**

0.513**

0.565**

0.576**

0.049

-0.111

-0.049

-0.084

0.017

Temp Sw. Symm

0.231

0.050

0.007

0.033

0.132

Tot Temp Symm

0.186

-0.025

-0.028

0.020

0.079

-0.027

-0.040

Temp St. Symm

Spatial Symm

0.798**

0.315*

0.194

Lt Temp Var %CV

0.615**

0.647**

Rt Temp Var %CV

0.482**

0.589**

* Correlation is significant at the 0.05 level (2-tailed) **Correlation is significant at the 0.01 level (2-tailed)

70

71

72 8.2 Appendix B: Results for Sub-Groups 8.2.1 Results for Etiology Groups

73 Table 15: Summary of Clinical Measures Results for Etiology Groups (significant findings indicated with an asterisk*)

Etiology

Measure LEMS

Baseline 10mWT

Baseline 6MWT

Baseline TUG

Baseline ADS

Baseline WISCI

Admission FIM

Baseline WMS

n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value

NTiSCI

TiSCI

33 0 – 49 40 37.33(±10.84)

15 13 – 50 30 33.07(±12.58) 0.275

11 0.14 – 0.95 0.51 0.51(±0.25)

4 0.55 – 1.27 0.77 0.84(±0.31) 0.068

13 24.0 – 355.0 178.41 188.48(±112.87)

6 99.5 – 318.0 237.63 209.46(±87.47) 0.629

9 13.7 – 131.00 31.00 39.68(±37.16)

3 8.89 – 15.50 12.81 12.40(±3.32) 0.033*

31 5 – 14 8 8.29(±2.10)

18 5 – 14 8 9.28(±2.63) 0.098

31 1 – 20 13 10.77(±5.01)

18 2 – 19 13 11.56(±4.48) 0.508

34 47 – 118 88.0 86.79(±16.72)

18 48 – 116 81.5 82.72(±19.73) 0.465

31 1–5 2 2.29(±1.13)

18 1–5 2 2.50(±1.30) 0.607

74

75

76 Table 16: Summary of Spatiotemporal results for Etiology Groups (significant findings indicated with an asterisk*) ETIOLOGY GROUPS

Parameter Velocity

Range Median Mean (±SD) p value Cadence Range Median Mean (±SD) p value Stance Time (%GC) Range Median Mean (±SD) p value Swing Time (%GC) Range Median Mean (±SD) p value Single Support Time (%GC) Range Median Mean (±SD) p value Double Support Time (%GC) Range Median Mean (±SD) p value Temporal Stance Symmetry Range Median Mean (±SD) p value Temporal Swing Symmetry Range Median Mean (±SD) p value Total Temporal Symmetry Range Median Mean (±SD) p value Spatial Step Symmetry Range Median Mean (±SD) p value Step Time Variability (%CV) Range Median Mean (±SD) p value Step Length Variability (%CV) Range Median Mean (±SD) p value

Non-Traumatic (n=34) Left

Traumatic (n=18)

Right

Left

0.13 – 1.45 0.57 0.58(±0.30)

Right

0.20 – 1.30 0.55 0.68(±0.35) 0.477

29.20-133.48 73.01 75.68(±24.12)

30.33-123.75 70.00 76.25(±26.27)

0.893 62.92-87.15 60.78-75.30 60.75-83.51 68.02 66.12 69.63 70.84(±6.76) 67.04(±4.01) 69.42(±5.61)1 Left p = 0.191 Right p= 0.644 13.46-38.08 12.85-37.06 24.70-39.22 16.51-39.25 32.83 31.95 33.88 30.37 30.14(±6.56) 29.16(±6.76) 32.96(±4.01) 30.59(±5.61) Left p = 0.191 Right p = 0.644 12.88-37.36 13.71-37.97 16.20-38.86 24.49-39.26 31.61 33.02 30.61 33.58 29.14(±6.77) 30.17(±6.52) 30.66(±5.52) 32.89(±4.14) Left p = 0.564 Right p = 0.178 25.56-78.03 26.50-73.33 26.01-52.66 26.38-53.12 37.01 37.54 34.89 35.10 41.47(±12.75) 41.09(±12.15) 36.69(±7.65) 36.58(±7.55) Left p = 0.265 Right p = 0.241 1.00-1.25 1.00-1.25 1.03 1.04 1.05(±0.06) 1.07(±0.08) 0.169 1.01-1.46 1.01-1.51 1.06 1.07 1.12(±0.13) 1.13(±0.14) 0.863 1.01-1.63 1.02-1.59 1.08 1.10 1.16(±0.18) 1.18(±0.17) 0.453 1.00-1.68 1.00-1.39 1.09 1.05 1.13(±0.14) 1.07(±0.09) 0.068 2.11-41.58 3.11-55.13 3.79-13.67 3.33-13.02 8.53 6.36 6.06 7.24 11.02(±8.85) 10.66(±6.36) 7.25(±2.97) 7.35(±2.40) Left p = 0.091 Right p = 0.939 2.27-42.95 1.71-24.40 2.71-14.33 2.09-11.73 9.43 8.28 7.38 5.94 10.61(±7.54) 9.66(±5.71) 7.20(±7.54) 6.15(±2.57) Left p = 0.071 Right p = 0.014* 61.96-86.57 67.19 69.86(±6.56)

77 8.2.2

Results for Level of Injury Groups

78 Table 17: Summary of Clinical Measures Results for LOI Groups (significant findings indicated with an asterisk*)

Level of Injury

Measure LEMS

Baseline 10mWT

Baseline 6MWT

Baseline TUG

Baseline ADS

Baseline WISCI

Admission FIM

Baseline WMS

n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value

Tetraplegia

Paraplegia

14 24 – 50 45.5 41.07(±10.13)

34 0 – 49 36.0 33.91(±11.45) 0.025*

5 0.51 – 1.27 0.75 0.81(±0.31)

10 0.14 – 0.80 0.51 0.49(±0.24) 0.086

6 99.50 – 341.56 237.63 216.39(±95.57)

13 24.0 – 355.00 178.41 185.28(±109.28) 0.510

3 8.89 – 15.50 14.7 13.03(±3.61)

9 12.81 – 131.00 31.0 39.47(±37.32) 0.079

17 6 – 14 8 9.06(±2.66)

32 5 – 14 8 8.44(±2.15) 0.533

17 4 – 20 8.0 10.47(±4.69)

32 1 – 20 13.0 11.38(±4.88) 0.502

17 47 – 107 82.0 79.71(±19.05)

35 58 – 118 89.0 88.14(±16.64) 0.184

17 1–5 2.0 2.47(±1..28)

32 1–5 2.0 2.31(±1.15) 0.704

79

80

81 Table 18: Summary of Spatiotemporal Results for LOI Groups (significant findings indicated with an asterisk*) Level of Injury Parameter Velocity

Range Median Mean (±SD) p value Cadence Range Median Mean (±SD) p value Stance Time (%GC) Range Median Mean (±SD) p value Swing Time (%GC) Range Median Mean (±SD) p value Single Support Time (%GC) Range Median Mean (±SD) p value Double Support Time (%GC) Range Median Mean (±SD) p value Temporal Stance Symmetry Range Median Mean (±SD) p value Temporal Swing Symmetry Range Median Mean (±SD) p value Total Temporal Symmetry Range Median Mean (±SD) p value Spatial Step Symmetry Range Median Mean (±SD) p value Stp Time Variability (%CV) Range Median Mean (±SD) p value Stp Length Variability (%CV) Range Median Mean (±SD) p value

Tetraplegia (n=17) Left

Paraplegia (n=35)

Right

Left

0.27-1.27 0.57 0.66(±0.30)

Right

0.13-1.45 0.55 0.59(±0.33) 0.441

41.45-123.75 85.28 83.00(±22.13)

29.20-133.48 72.48 72.42(±25.33)

0.181 62.06-73.37 60.75-83.51 60.78-86.57 61.16-87.15 67.24 67.18 66.57 69.24 67.97(±3.20) 68.27(±5.24) 69.33(±6.87) 71.36(±6.69) Left p = 0.822 Right p= 0.095 26.63-37.94 16.51-39.25 13.46-39.22 12.85-38.85 32.77 32.84 33.43 30.76 32.04(±3.20) 31.73(±5.24) 30.67(±6.87) 28.64(±6.69) Left p = 0.838 Right p = 0.095 16.20-18.86 26.29-37.46 12.88-38.40 13.71-39.26 33.23 32.92 30.90 33.48 31.71(±5.22) 32.07(±3.32) 28.68(±6.68) 30.64(±6.81) Left p = 0.099 Right p = 0.961 26.63-52.66 26.87-53.12 25.56-78.03 26.38-73.33 34.02 33.78 36.58 37.42 36.86(±7.10) 36.60(±6.74) 41.25(±12.84) 40.95(±12.29) Left p = 0.385 Right p = 0.441 1.01 – 1.21 1.00 – 1.25 1.03 1.04 1.05(±0.06) 1.06(±0.07) 0.725 1.01 – 1.51 1.01 - 1.46 1.04 1.08 1.10(±0.14) 1.13(±0.13) 0.195 1.01-1.59 1.01-1.63 1.06 1.13 1.15(±0.18) 1.18(±0.18) 0.619 1.00-1.29 1.00-1.68 1.05 1.08 1.09(±0.08) 1.12(±0.14) 0.507 4.53-26.69 3.67-21.75 2.11-41.58 3.11-55.13 7.93 7.53 7.62 6.41 9.08(±5.86) 8.48(±4.85) 10.02(±8.30) 10.01(±9.98) Left p = 0.992 Right p = 0.930 2.59-26.25 1.71-21.74 2.27-42.95 2.09-24.40 9.66 7.60 7.73 6.95 10.17(±5.82) 8.90(±5.31) 9.06(±6.93) 8.23(±5.08) Left p = 0.418 Right p = 0.661

82 8.2.3

Results for Severity of Injury Groups

83 Table 19: Summary of Clinical Measures Results for SOI Groups (significant findings indicated with an asterisk*)

Severity of Injury Measure LEMS

Baseline 10mWT

Baseline 6MWT

Baseline TUG

Baseline ADS

Baseline WISCI

Admission FIM

Baseline WMS

n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value n Range Median Mean (±SD) p value

AIS C

AIS D

7 13.00-24.00 20.0 19.00(±4.24)

40 25.00-50.00 41.00 39.88(±7.40) 0.000*

0 14 no data 0.14-1.27 no data 0.60 no data 0.63(±0.29) Inadequate data 2 16 24.0 – 45.0 88.6 – 355.0 34.5 237.6 34.5(±14.85) 221.38(±89.55) 0.025* 0 11 no data 8.89-131.00 no data 18.41 no data 30.39(±34.55) Inadequate data 9 39 5 - 14 5 - 14 8.0 8.0 7.78(±2.59) 8.87(±2.28) 0.053 9 39 2 – 13 1 – 20 7.0 13.0 6.89(±3.02) 11.97(±4.69) 0.003* 9 42 48.0 – 84.0 47.0 – 118.0 69.0 90.0 70.33(±12.30) 88.88(±17.21) 0.003* 9 39 1–4 1–5 1.0 3.0 1.33(±1.00) 2.59(±1.12) 0.002*

84

85

86 Table 20: Summary of Spatiotemporal Results for SOI Groups (significant findings indicated with an asterisk*)

Severity of Injury

Parameter Velocity

Range Median Mean (±SD) p value Cadence Range Median Mean (±SD) p value Stance Time (%GC) Range Median Mean (±SD) p value Swing Time (%GC) Range Median Mean (±SD) p value Single Support Time (%GC) Range Median Mean (±SD) p value Double Support Time (%GC) Range Median Mean (±SD) p value Temporal Stance Symmetry Range Median Mean (±SD) p value Temporal Swing Symmetry Range Median Mean (±SD) p value Total Temporal Symmetry Range Median Mean (±SD) p value Spatial Step Symmetry Range Median Mean (±SD) p value Stp Time Variability (%CV) Range Median Mean (±SD) p value Stp Length Variability (%CV) Range Median Mean (±SD) p value

AIS C (n=9) Left

AIS D (n=42) Right

Left

0.18-1.07 0.55 0.62(±0.29)

Right

0.13-1.45 0.56 0.62(±0.33) 0.805

45.87-99.73 71.35 72.65(±17.38) 62.98-86.57 68.62 71.23(±7.16) 13.46-37.02 31.38 28.76(±7.15) 13.08-35.23 31.08 29.30(±6.87) 30.70-78.03 39.20 42.65(±14.73)

29.20-133.48 73.01 76.61(±26.31)

0.553 64.77-87.15 60.78-85.42 69.24 66.63 70.83(±7.00) 68.44(±5.66) Left p = 0.166 Right p= 0.980 12.85-35.21 14.59-39.22 30.76 33.37 29.18(±7.00) 31.56(±5.66) Left p = 0.174 Right p = 0.980 13.71-37.07 12.88-38.86 31.21 30.98 28.70(±7.13) 29.58(±6.30) Left p = 1.000 Right p = 0.159 31.18-73.33 25.56-71.25 38.25 35.68 42.18(±13.21)

39.45(±10.72)

60.75-86.97 68.65 70.42(±6.29) 13.04-39.25 31.34 29.58(±6.29) 14.93-39.26 33.51 31.57(±5.64) 26.38-72.33 36.42 39.20(±10.50)

Left p = 0.587 Right p = 0.505 1.01 – 1.12 1.00 – 1.25 1.03 1.03 1.04(±0.03) 1.06(±0.07) 0.941 1.01 – 1.34 1.01 – 1.51 1.06 1.07 1.09(±0.10) 1.13(±0.14) 0.505 1.01 – 1.52 1.01 – 1.63 1.09 1.09 1.13(±0.15) 1.18(±0.18) 0.824 1.00 – 1.33 1.00 – 1.68 1.14 1.06 1.12(±0.10) 1.11(±0.13) 0.415 3.79-41.58 3.67-28.09 2.11-34.97 3.11-55.13 6.18 6.11 8.23 7.01 10.11(±11.96) 8.65(±7.50) 9.73(±6.51) 9.77(±8.99) Left p = 0.166 Right p = 0.621 2.59-11.65 1.71-24.40 2.27-42.95 2.09-22.43 8.54 5.71 8.79 7.51 7.42(±3.39)

7.87(±6.98)

9.97(±7.04)

Left p = 0.361 Right p = 0.246

8.65(±4.76)

87 8.2.4

Results for Gait Aid Groups 8.2.4.1 Stratification of Total Population

88 Table 21: Summary of Clinical Measures Results for Gait Aid groups (significant findings indicated with an asterisk*)

GAIT AID GROUP Measure LEMS

n Range Median Mean (±SD) p value Base 10mWT n Range Median Mean (±SD) p value Base 6MWT n Range Median Mean (±SD) p value Base TUG n Range Median Mean p(±SD) value Base ADS n Range Median Mean (±SD) p value Base WISCI n Range Median Mean (±SD) p value Adm FIM n Range Median Mean (±SD) p value Base WMS n Range Median Mean (±SD) p value

Walker

2 SPCs

1 SPC

No Aid

24 20.0 – 50.0 37.0 36.71(±8.38)

7 15.0 – 50.0 31.0 31.29(±13.79)

7 0.0 – 49.0 43.0 38.14(±17.16)

10 13.0 – 48.0 39.5 36.10(±12.66)

2 0.25 – 0.80 0.53 0.53(±0.39)

3 0.64 – 0.79 0.69 0.41(±0.08)

3 96.00 – 355.00 318.00 256.33(±140.08)

4 209.61 – 315.00 255.05 258.68(±43.26)

2 18.41 – 60.00 39.21 39.21(±29.41)

3 12.81 – 19.50 13.7 15.34(±3.63)

9 8 – 14 8.0 9.67(±2.55)

11 6 – 14 8.0 9.36(±2.98)

9 7 – 20 13.0 13.56(±4.36)

11 2 – 20 13.0 12.09(±5.75)

9 48.0 – 118.0 86.0 90.44(±22.80)

11 49.0 – 107 84.0 82.09(±18.28)

9 1–4 3.0 2.67(±1.00)

11 1–5 2.0 2.82(±1.60)

0.529 10 0.14 – 1.27 0.53 0.58(±0.33)

0 no data no data no data 0.600

10 45.00 – 341.56 170.19 177.23(±94.54

2 24.00 – 107.00 65.5 65.5(±58.69) 0.157

7 8.89 – 131.00 31.00 38.55(±42.08)

0 no data no data no data 0.334

22 5 – 14 8.0 7.95(±1.94)

7 7 – 12 8.0 8.43(±1.62) 0.115

22 1 – 20 12.0 9.86(±4.56)

7 6 – 16 8.0 10.00(±3.51) 0.194

25 47.0 – 108.0 89.0 86.04(±16.15)

7 58.0 – 101.0 82.0 81.71(±17.43) 0.666

22 1–4 2.5 2.18(±1.01)

7 1–4 2.0 1.86(±1.07) 0.339

89

90

91 Table 22: Summary of Spatiotemporal Results for Gait Aid groups (significant findings indicated with an asterisk*) GAIT AID GROUPS Walker (n=25) Left

Parameter Velocity

Cadence

Right

Range Median Mean (±SD) p value p value WALKER p value 2SPC p value 1SPC

0.13 – 1.04 0.49 0.48(±0.23)

Range Median Mean (±SD) p value p value WALKER p value 2SPC p value 1SPC

29.20 – 115.90 62.80 65.77(±21.80)

Stance Time (%GC)

Range Median Mean (±SD) p value p value WALKER p value 2SPC p value 1SPC

Swing Time (%GC)

Range Median Mean (±SD) p value p value WALKER p value 2SPC p value 1SPC

Single Support Time (%GC) Range

Median Mean (±SD) p value p value WALKER p value 2SPC p value 1SPC Double Support Time (%GC) Range

Median Mean (±SD) p value p value WALKER p value 2SPC p value 1SPC

2 SPCs (n=7) Left

1 SPC (n=9)

Right

Left

0.18 – 0.61 0.42 0.39(±0.17)

Right

No Aid (n=11) Left

Right

0.47 – 1.45 0.65 0.75(±0.33)

0.58 – 1.30 0.97 0.96(±0.21)

1.000

0.130 0.126

30.33 – 87.50 59.54 60.21(±18.23)

67.60 – 133.48 74.27 84.33(±21.30)

0.000* 0.001* 0.935 85.28 – 123.75 99.73 101.91(±12.36)

0.000**

0.000** 1.000

0.333 0.309

0.000* 0.002* 0.509

60.78-85.42

60.75-86.97

66.08-86.57

67.18-87.15

62.79-73.20

61.16-74.09

61.96-72.45

62.92-67.47

67.24

73.32

72.43

71.31

66.47

67.28

65.62

65.57

69.77(±6.64)

72.79(±6.68)

73.28(±6.75)

73.24(±6.58)

66.55(±3.30)

67.34(±4.51)

65.99(±2.70)

65.44(±1.44)

Left p= 0.033* Right p= 0.001* Left p=0.791Right p=1.000

Left p= 1.000 Right p=0.161

Left p=0.413 Right p=0.003*

Left p=0.165 Right p=0.323

Left p=0.402* Right p=0.026* Left p=1.000 Right p=1.000

14.59-39.22

13.04-39.25

13.46-33.94

12.85-32.84

26.80-37.23

25.91-38.85

27.55-38.08

32.56-37.06

32.77

26.69

27.57

28.69

33.52

32.69

34.43

34.45

30.23(±6.64)

27.12(±6.68)

26.73(±6.74)

26.77(±6.59)

33.45(±3.30)

32.66(±4.51)

34.02(±2.71)

34.56(±1.43)

Left p = 0.033* Right p = 0.001* Left p=0.791 Right p=1.000

Left p=1.000 Right p=0.161

Left p=0.384 Right p=0.003*

Left p=0.177 Right p=0.323

Left p=0.039 Right p=0.026* Left p=1.000 Right p=1.000

12.88-38.86

14.93-39.26

13.08-33.23

13.71-33.54

26.42-38.40

26.29-37.50

32.51-37.36

27.32-37.97

26.61

32.92

29.51

26.80

32.64

33.56

34.48

34.27

27.13(±6.69)

30.31(±6.59)

27.08(±6.64)

26.49(±6.53)

32.72(±4.29)

33.38(±3.49)

34.58(±1.33)

34.01(±2.78)

Left p = 0.001* Right p = 0.027* Left p=1.000 Right p=0.479

Left p=0.114 Right p=1.000

Left p=0.002* Right p=0.528

Left p=0.321 Right p=0.116

Left p=0.030* Right p=0.028

25.56-46.49

29.08-35.11

Left p=1.000 Right p=1.000 26.63-71.25

26.87-72.33

33.94-78.03

33.30-73.33

26.38-45.19

28.87-35.14

40.81

41.20

45.19

43.67

33.77

33.13

31.40

31.22

43.20(±11.41)

43.05(±11.38)

48.08(±14.87)

46.56(±13.13)

33.75(±6.58)

33.81(±6.05)

31.84(±1.85)

31.74(±1.65)

Left p = 0.000** Right p = 0.000** Left p=1.000 Right p=1.000

Left p=0.102 Right p=0.102

Left p=0.003*Right p=0.003*

Left p=0.071 Right p=0.097

Left p=0.006* Right p=0.008 Left p=1.000 Right p=1.000

92 Table 22 Continued: Summary of Spatiotemporal Results for Gait Aid Groups (significant findings indicated with an asterisk*) GAIT AID GROUPS

Parameter Temporal Stance Symmetry Range

Median Mean (±SD) p value

Temporal Swing Symmetry Range

Median Mean (±SD) p value Total Temp. Symmetry

Range Median Mean (±SD) p value

Spatial Step Symmetry

Range Median Mean (±SD) p value

Range Median Mean (±SD) p value p value WALKER p value 2SPC p value 1SPC

Stp Time Variability (%CV)

Stp Length Variability (%CV) Range

Median Mean (±SD) p value p value WALKER p value 2SPC p value 1SPC

Walker (n=25)

2 SPCs (n=7)

1 SPC (n=9)

No Aid (n=11)

Left Right 1.00 – 1.25 1.03 1.08(±0.08)

Left Right 1.01 – 1.04 1.02 1.02(±0.01)

Left Right 1.00 – 1.17 1.03 1.05(±0.05)

Left Right 1.00 – 1.12 1.04 1.04(±0.04)

1.01 – 1.28 1.10 1.09(±0.08)

1.01 – 1.36 1.05 1.08(±0.10)

1.02 – 1.38 1.14 1.13(±0.11)

1.01 – 1.55 1.09 1.13(±0.15

1.00 – 1.15 1.05 1.07(±0.06)

1.00 – 1.27 1.03 1.09(±0.09)

0.416 1.01 – 1.51 1.12 1.17(±0.16)

1.02 – 1.07 1.04 1.04(±0.02) 0.085

1.02 – 1.63 1.14 1.23(±0.21)

1.03 – 1.10 1.05 1.06(±0.03) 0.156

1.00 – 1.68 1.07 1.13(±0.56)

1.02 – 1.33 1.07 1.13(±0.11) 0.483

4.53-34.97

3.95-55.13

4.29-41.58

5.97-28.09

3.27-10.77

3.67-9.04

2.11-9.08

3.11-12.27

9.57

7.08

11.23

10.08

7.09

6.32

5.58

5.44

11.12(±7.81)

11.28(±11.01

13.78(±12.71)

13.11(±7.85)

7.30(±2.43)

6.45(±1.98)

5.90(±2.07)

5.71(±2.50)

Left p = 0.032* Right p = 0.014* Left p=1.000 Right p=1.000

Left p=1.000 Right p=1.000

Left p=0.056 Right p=0.112

Left p=0.998 Right p=0.209

Left p=0.102 Right p=0.020* Left p=1.000 Rt p=1.000

3.28-42.95

4.06-22.43

4.13-14.33

4.91-24.40

3.28-13.57

2.44-11.73

2.27-15.97

1.71-12.05

9.69

8.02

10.74

7.91

6.21

5.22

7.15

6.18

11.18(±8.23)

9.75(±5.01)

10.13(±3.62)

10.93(±7.33)

7.28(±3.94)

6.34(±3.28)

6.74(±4.03)

5.64(±3.31)

Left p= 0.069 Right p= 0.025* Right p=1.000

Right p=0.228

Right p=0.067

Right p=0.654

Right p=0.343 Right p=1.000

93 8.2.4.2 Results for “No Aid” Group

94

95

96

Table 23: Summary of Clinical Measures results for "No Aid" Group (significant findings indicated with an asterisk; unable to calculate (utc)) STRATIFICATION RESULTS FOR NO GAIT AID GROUP Etiology

Measure LEMS Range Median Mean (±SD) p value 10mWT Range Median Mean (±SD) p value 6MWT Range Median Mean (±SD) p value TUG Range Median Mean (±SD) p value ADS Range Median Mean (±SD) p value WISCI Range Median Mean (±SD) p value Adm FIM Range Median Mean (±SD) p value WMS Range Median Mean (±SD) p value

Level of Injury

Severity of Injury

Tetra

AIS C

Velocity Groups

Temp. Symmetry Groups

Spat. Symmetry Groups

Temp. Variability Groups

Spatial Variability Groups

Symm

Low

Low

n=6

n=4

n=4

n=6

n=3

n=7

n=1

n=2

n=7

n=5

n=4

Sev. Asym n=1

n=7

n=3

n=5

n=5

24.0-48.0

13.0-48.0

24.0-48.0

13.0-48.0

13.0-24.0

30.0-48.0

47.0-47.0

24.0-48.0

13.0-48.0

24.0-48.0

13.0-48.0

47.0-47.0

13.0-48.0

24.0-48.0

13.0-48.0

24.0-48.0

44.50

27.00

35.50

39.50

24.00

47.00

47.0

36.0

37.0

37.0

33.0

47.0

37.0

47.0

30.0

42.0

41.00 (±9.38)

28.75 (±14.64)

35.50 (±13.57)

36.33 (±13.34)

20.33 (±6.35)

42.86 (±7.03)

47.00 (±n/a)

36.00 (±16.97)

34.57 (±13.04)

37.40 (±10.71)

31.75 (±16.13)

47.0 (±n/a)

34.57 (±13.04)

39.67 (±13.58)

32.60 (±15.32)

39.60 (±9.76)

n=0 Ø data Ø data Ø data

0.847 n=0 Ø data Ø data Ø data

n=3

n=2

0.709 n=1

n=2

n=1

n=2

0.671 n=1

0.64-0.79

0.69-0.79

0.64-0.64

0.69-0.79

0.64-0.64

0.64-0.79

0.69-0.69

0.69

0.74

0.64

0.74

0.64

0.72

0.69

0.71 (±0.08)

0.74 (±0.07)

0.64 (±n/a)

n=0 Ø data Ø data Ø data

0.74 (±0.07)

0.64 (±n/a)

0.72 (±0.11)

0.69 (±n/a)

utc n=1

n=3

n=3

0.221 n=1

n=3

n=1

n=2

1.000 n=2

315.00315.00

209.61257.00

209.61315.00

253.10253.10

209.61315.00

253.10253.10

253.1257.0

209.61315.00

315.00

253.10

257.00

253.10

253.10

255.05

262.31

239.90 (±26.31)

260.54 (±52.78)

253.10 (±n/a)

Ø data Ø data

257.00

315.00 (±n/a)

260.54 (±52.78)

253.10 (±n/a)

255.05 (±2.76)

262.31 (±74.52)

n=3

n=2

0.655 n=1

n=0 Ø data

n=2

n=1

n=2

1.000 n=1

12.8119.50

13.7013.70

12.8113.70

19.5019.50

Ø data Ø data

16.16

13.70

13.26

19.50

16.16 (±4.73)

13.70 (±n/a)

13.26 (±0.63)

19.50 (±n/a)

n=0 Ø data Ø data Ø data

NTiSCI

TiSCI

0.234 n=2

n=1

0.64-0.69

0.79-0.79

0.67

0.79

0.67 (±0.04)

0.79 (±n/a)

0.221 n=3

n=1

209.61315.00

257.00257.00

253.10

257.00

259.24 (±52.96)

257.00 (±n/a)

0.655 n=2

n=1

13.7019.50

12.8112.81

16.60

12.81

16.60 (±4.10)

12.81 (±n/a)

0.221

Para

0.829 n=0 n=3 0.64-0.79 Ø data Ø data 0.69 0.71 Ø data (±0.08) utc n=0 n=4 209.61Ø data 315.00 Ø data 255.05 258.68 Ø data (±43.26) utc n=0 n=3 12.81Ø data 19.50 Ø data 13.70 15.34 Ø data (±3.63) utc n=4 n=7

AIS D

0.015* n=0 n=3 0.64-0.79 Ø data Ø data 0.69 0.71 Ø data (±0.08) utc n=0 n=4 209.61Ø data 315.00 Ø data 255.05 258.68 Ø data (±43.26) utc n=0 n=3 12.81Ø data 19.50 Ø data 13.70 15.34 Ø data (±3.63) utc n=3 n=8

VSv

n=0 Ø data Ø data Ø data

Sv

Mv

Symm

Asym

Asym

0.643

0.221 n=0 Ø data

High n=0 Ø data Ø data Ø data n=0 Ø data Ø data Ø data n=0 Ø data Ø data Ø data

Mod.

High n=0 Ø data Ø data Ø data

n=4

n=6

13.0-48.0

24.0-48.0

27.0

44.5

28.75 (±14.64)

41.00 (±9.38)

n=2

0.234 n=1

0.64-0.79

0.69-0.69

0.72

0.69

0.72 (±0.11)

0.69 (±n/a)

n=2

1.000 n=2

253.1257.0

209.61315.00

255.05

262.31

255.05 (±2.76)

262.31 (±74.52)

n=2

1.000 n=1

12.8113.70

19.5019.50

13.26

19.50

13.26 (±0.63)

19.50 (±n/a)

n=0 Ø data Ø data Ø data n=0 Ø data Ø data Ø data

12.8119.50

12.8119.50

13.7013.70

13.70

16.16

13.70

15.34 (±3.63)

16.16 (±4.73)

13.70 (±n/a)

n=1

0.180 n=0 Ø data Ø data Ø data utc n=3

n=7

n=6

1.000 n=4

n=1

n=7

n=4

n=5

0.221 n=5

n=1

n=4

0.221 n=6

n=1

8.0-8.0

8.0-8.0

6.0-14.0

6.0-14.0

6.0-14.0

8.0-8.0

6.0-14.0

6.0-14.0

6.0-14.0

8.0-10.0

8.0-8.0

6.0-14.0

8.0-14.0

8.0-8.0

n=0 Ø data Ø data Ø data

0.655

Mod.

1.000

n=0 Ø data Ø data Ø data

n=7

n=4

6.0-14.0

6.0-14.0

8.00

10.50

8.00

8.00

6.00

9.00

8.00

8.00

10.00

9.00

8.00

8.00

8.00

8.00

13.00

8.00

8.00

9.50

8.00

8.0

8.86 (±2.54)

10.25 (±3.86)

9.00 (±3.46)

9.57 (±2.94)

6.67 (±1.15)

10.37 (±2.83)

8.00 (±n/a)

8.00 (±0.00)

10.14 (±3.58)

9.83 (±3.13)

9.00 (±3.46)

8.00 (±n/a)

9.57 (±2.94)

9.00 (±3.46)

10.60 (±4.22)

8.40 (±0.89)

8.00 (±n/a)

9.75 (±4.35)

9.33 (±2.33)

8.00 (±n/a)

6.0-14.0

0.690

6.0-14.0

6.0-8.0

0.690

8.0-14.0

n=7

n=4

n=4

n=7

n=3

n=8

n=1

0.728 n=3

n=7

n=6

0.838 n=4

n=1

n=7

n=4

n=5

0.834 n=5

n=1

n=4

0.877 n=6

n=1

5-20

2-17

5-17

2-20

2-8

8-20

8-8

8-19

2-20

5-19

2-20

8-8

2-19

5-20

2-20

8-19

13-13

2-20

8-19

13-13

13.0

11.5

8.0

13.0

5.0

14.0

8.0

13.0

13.0

14.0

10.5

8.0

13.0

10.5

15.00

13.00

13.0

10.0

13.0

13.0

13.00 (±5.39)

10.50 (±6.86)

9.50 (±5.20)

13.57 (±5.88)

5.00 (±3.00)

14.75 (±3.88)

8.00 (±n/a)

13.33 (±5.51)

12.14 (±6.44)

13.67 (±4.84)

10.50 (±7.63)

8.00 (±n/a)

12.43 (±5.77)

11.50 (±6.56)

11.80 (±7.86)

12.20 (±4.55)

13.00 (±n/a)

10.50 (±8.43)

13.00 (±4.52)

13.00 (±n/a)

0.717 n=3

n=7

n=6

0.573 n=4

n=1

n=7

n=4

n=5

0.982 n=5

n=1

n=4

0.925 n=6

n=1

0.633

0.031*

0.251

n=7

n=4

71.0107.0

49.0-82.0

89.00 91.71 (±12.88)

0.018*

0.690

0.774

n=4

n=7

n=3

n=8

n=1

49.0-84.0

62.0107.0

68.0-84.0

49.0107.0

71.0-71.0

68.0107.0

49.0106.0

49.0107.0

68.0106.0

71.0-71.0

49.0107.0

71.0-89.0

49.0-87.0

68.0107.0

89.0

62.0-87.0

49.0107.0

89.0

65.00

69.50

89.00

82.00

88.00

47.00

89.00

84.00

86.50

84.50

71.00

82.00

85.50

82.00

98.00

89.00

83.00

84.50

89.00

65.25 (±13.70)

68.00 (±14.45)

90.14 (±15.64)

78.00 (±8.72)

83.63 (±21.11)

47.00 (±n/a)

88.00 (±19.52)

81.14 (±19.77)

81.50 (±22.01)

85.75 (±15.71)

71.00 (±n/a)

81.71 (±22.88)

82.75 (±8.10)

72.80 (±16.54)

90.00 (±19.07)

89.00 (±n/a)

78.75 (±11.35)

83.17 (±23.90)

89.00 (±n/a)

n=1

n=7

0.014* n=4

n=4

n=7

n=3

n=8

n=1

0.637 n=3

n=7

n=6

0.818 n=4

n=1

n=7

n=4

n=5

0.256 n=5

n=1

n=4

0.674 n=6

1-5

1-5

1-5

1-5

1-1

2-5

2-2

1-4

1-5

1-5

1-5

2-2

1-5

1-5

1-5

1-4

4-4

1-5

1-5

4-4

2.0

2.5

1.5

4.0

1.0

4.0

2.0

4.0

2.0

4.0

1.5

2.0

2.0

3.0

4.0

2.0

4.0

2.5

2.0

4.0

2.86 (±1.47)

2.75 (±2.06)

2.25 (±1.89)

3.14 (±1.46)

1.00 (±0.00)

3.50 (±1.31)

2.00 (±n/a)

3.00 (±1.73)

2.86 (±1.77)

3.33 (±1.51)

2.25 (±1.89)

2.00 (±n/a)

2.71 (±1.60)

3.00 (±1.83)

3.20 (±2.05)

2.20 (±1.10)

4.00 (±n/a)

2.75 (±2.06)

2.67 (±1.51)

4.00 (±n/a)

0.770

0.059

0.381

0.414

0.012*

0.946

0.585

0.850

0.770

0.593

0.801

97

Table 24: Summary of Spatiotemporal Measures Results for "No Aid" Group (significant findings indicated with an asterisk; unable to calculate (utc)) STRATIFICATION RESULTS FOR “NO AID” GROUP Etiology

Measure n Velocity: Range Median Mean (±SD) p value Cadence: Range Median Mean (±SD) p value Lt. St %GC: Range Median Mean (±SD) p value Rt. St %GC: Range Median Mean (±SD) p value Lt. Sw %GC: Range Median Mean (±SD) p value Rt. Sw %GC: Range Median Mean (±SD) p value Lt. SS %GC: Range Median Mean (±SD) p value Rt. SS %GC: Range Median Mean (±SD) p value Lt. DS %GC: Range Median Mean (±SD) p value Rt. DS %GC: Range Median Mean (±SD) p value

Level of Injury

Severity of Injury

NTiSCI 7

TiSCI 4

Tetra 4

Para 7

AIS C 3

AIS D 8

0.58-1.07

0.81-1.30

0.58-1.27

0.73-1.30

0.81-1.07

0.97

1.10

0.94

0.97

0.93

0.89(±0.18)

1.08(±0.24)

0.93(±0.58)

0.97(±0.18)

0.94(±0.13)

0.345

0.850

Velocity Groups VSv 1

Sv 3

Temp. Symmetry Groups Mv 7

Spat. Symm Groups

Temp. Variability Groups

Spatial Variability Groups

1

Symm 7

Asym 4

Low 5

Mod. 5

High 1

Low 4

Mod. 6

High 1

0.81-1.01

0.58-0.58

0.81-1.30

0.58-1.07

0.93-1.30

0.58-1.01

0.73-0.73

0.93-1.30

0.58-1.27

0.73-0.73

0.95

0.58

1.01

0.85

1.07

0.84

0.73

1.02

0.92

0.73

1.04(±0.23)

0.93(±0.09)

0.58(±n/a)

1.02(±0.19)

0.84(±0.22)

1.11(±0.17)

0.85(±0.18)

0.73(±n/a)

1.07(±0.16)

0.92(±0.23)

0.73(±n/a)

Symm 6

Asym 4

Sev Asym

0.58-1.30

0.73-1.30

0.99

1.04

0.96(±0.25)

0.838

0.178

0.257

0.103

0.259

85.55-109.60

85.28-123.75

85.28-123.75

85.55-118.88

85.28-99.73

85.55-123.75

96.23-96.23

85.28-98.12

93.27-123.75

85.55-123.75

85.28-107.53

96.23-96.23

85.28-123.75

96.23-103.13

93.27-123.75

85.28-109.60

98.12-98.12

93.27-118.88

85.28-123.75

99.73

106.07

97.98

103.13

93.27

105.33

96.23

85.55

107.53

104.66

98.20

96.23

107.53

98.92

103.13

96.23

98.12

101.43

101.88

98.12

99.98(±8.01)

105.29(±18.89)

101.24(±16.22)

102.29(±11.07)

92.76(±7.24)

105.35(±12.40)

96.23(±n/a)

89.65(±7.34)

107.98(±10.63

105.94(±14.24)

97.30(±9.99)

96.23(±n/a)

103.41(±15.59)

99.30(±2.93)

107.75(±12.99)

96.84(±11.60)

98.12(±n/a)

103.75(±10.88)

101.32(±15.11)

98.12(±n/a)

0.850

0.705

0.102

0.072

0.433

0.705

0.441

98.12-98.12

0.906

61.96-72.45

62.98-67.86

65.00-72.45

61.96-66.57

62.98-67.86

61.96-72.45

72.45-72.45

65.25-67.86

61.96-66.57

65.00-66.50

61.96-67.86

72.45-72.45

62.98-67.86

61.96-72.45

61.96-66.16

65.25-72.45

66.50-66.50

61.96-66.16

65.25-72.45

65.53

65.89

66.74

65.53

65.00

65.89

72.45

66.50

65.53

65.58

64.77

72.45

65.62

65.75

65.00

66.57

66.50

63.99

66.10

66.50

66.18(±3.16)

65.66(±2.02)

67.73(±3.38)

64.99(±1.81)

65.28(±2.45)

66.26(±2.90)

72.45(±n/a)

66.54(±1.31)

64.83(±1.71)

65.68(±0.56)

64.84(±2.82)

72.45(±n/a)

65.71(±1.49)

66.48(±4.41)

64.35(±1.80)

67.53(±2.94)

66.50(±n/a)

64.03(±1.90)

67.21(±2.74)

66.50(±n/a)

0.850

0.257

0.540

0.149

0.287

0.850

0.133

66.50-66.50

0.114

62.92-67.38

64.25-67.47

62.92-65.17

63.76-67.47

64.77-67.47

62.92-67.38

62.92-92.92

64.77-67.38

63.76-67.47

64.25-67.38

63.76-67.47

62.92-62.92

63.76-67.47

62.92-66.26

64.25-67.47

62.92-67.38

66.25-66.25

65.17-67.47

62.92-67.38

66.10

65.17

64.51

66.25

65.17

65.84

62.92

66.25

65.57

65.84

65.52

62.92

65.57

65.71

65.57

64.77

66.25

65.92

64.51

66.25

65.41(±1.57)

65.52(±1.41)

64.28(±0.98)

66.11(±1.25)

65.81(±1.46)

65.31(±1.51)

62.92(±n/a)

66.13(±1.31)

65.51(±1.26)

65.79(±1.06)

65.57(±1.63)

62.92(±n/a)

65.62(±1.46)

65.15(±1.57)

65.75(±1.21)

64.99(±1.79)

66.25(±n/a)

66.12(±1.01)

64.86(±1.63)

66.25(±n/a)

1.000

0.038*

0.683

0.250

0.287

0.850

0.520

66.25-66.25

0.259

27.55-38.08

32.14-37.02

27.55-35.00

33.43-38.08

32.14-37.02

27.55-38.08

27.55-27.55

32.14-34.75

33.43-38.08

33.52-35.00

32.14-38.08

27.55-27.55

32.14-37.02

27.55-38.08

33.81-38.08

27.55-34.75

33.52-33.52

33.81-38.08

27.55-34.75

34.47

34.12

33.28

34.47

35.00

34.12

27.55

33.52

34.47

34.45

35.23

27.55

34.43

34.26

35.00

33.43

33.52

36.01

33.93

33.52

33.83(±3.17)

34.35(±2.03)

32.28(±3.39)

35.01(±1.82)

34.72(±2.45)

33.75(±2.91)

27.55(±n/a)

33.47(±1.31)

35.18(±1.72)

34.33(±0.56)

35.17(±2.83)

27.55(±n/a)

34.29(±1.49)

33.53(±4.42)

35.67(±1.81)

32.47(±2.94)

33.52(±n/a)

35.98(±1.93)

32.79(±2.75)

33.52(±n/a)

0.850

0.257

0.540

0.149

0.287

0.850

0.133

33.52-33.52

0.114

32.64-37.06

32.56-35.77

34.85-37.06

32.56-36.24

32.56-35.21

32.64-37.06

37.06-37.06

32.64-35.21

32.56-36.24

32.64-35.77

32.56-36.24

37.06-37.06

32.56-36.24

33.76-37.06

32.56-35.77

32.64-37.06

33.78-33.78

32.56-34.84

32.64-37.06

33.90

34.83

35.49

33.78

34.85

34.18

37.06

33.78

34.45

34.18

34.49

37.06

34.45

34.31

34.45

35.21

33.78

34.11

35.49

33.78

34.60(±1.56)

34.50(±1.40)

35.72(±0.97)

33.90(±1.24)

34.20(±1.44)

34.70(±1.50)

37.06(±n/a)

33.87(±1.29)

34.50(±1.26)

34.23(±1.06)

34.44(±1.62)

37.06(±n/a)

34.40(1.45)

34.86(±1.55)

34.28(±1.21)

35.01(±1.78)

33.78(±n/a)

33.90(±1.01)

35.14(±1.62)

33.78(±n/a)

1.000

0.038*

0.683

0.250

0.287

0.850

0.520

33.78-33.78

0.259

32.96-37.36

32.51-35.23

34.48-37.36

32.51-35.80

32.51-35.23

32.96-37.36

37.36-37.36

32.96-35.23

32.51-35.80

32.96-35.20

32.51-35.80

37.36-37.36

32.51-35.80

33.86-37.36

32.51-35.20

32.96-37.36

34.19-34.19

32.51-34.66

32.96-37.36

34.19

34.93

35.21

34.10

34.48

34.42

37.36

34.19

34.48

34.33

34.54

37.36

34.66

34.33

34.48

35.23

34.19

34.17

35.21

34.19

34.68(±1.45)

34.40(±1.28)

35.57(±1.24)

34.01(±1.08)

34.07(±1.40)

34.77(±1.35)

37.36(±n/a)

34.13(±1.13)

34.37(±1.05)

34.27(±0.75)

34.35(±1.47)

37.36(±n/a)

34.35(±1.23)

34.97(±1.61)

34.14(±1.03)

35.09(±1.67)

34.19(±n/a)

33.88(±0.97)

35.11(±1.49)

34.19(±n/a)

0.850

0.059

0.683

0.285

0.281

0.850

0.549

34.19-34.19

0.337

27.32-37.97

32.12-37.07

27.32-35.37

33.12-37.97

32.12-37.07

27.32-37.97

27.32-27.32

32.12-34.41

33.61-37.97

33.12-35.37

32.12-37.97

27.32-27.32

32.12-37.07

27.32-37.97

33.61-37.97

27.32-34.41

33.12-33.12

33.61-37.97

27.32-34.99

34.27

34.30

33.56

34.27

35.37

34.06

27.32

33.12

34.99

34.34

35.46

27.32

34.27

34.24

35.37

33.85

33.12

36.22

34.06

33.12

33.76(±3.24)

34.45(±2.10)

32.45(±3.71)

34.90(±1.86)

34.85(±2.51)

33.69(±2.97)

27.32(±n/a)

33.22(±1.15)

35.30(±1.65)

34.29(±0.84)

35.25(±2.74)

27.32(±n/a)

34.33(±1.50)

33.45(±4.54)

35.80(±1.73)

32.39(±2.98)

33.12(±n/a)

36.01(±1.93)

32.83(±2.87)

33.12(±n/a)

1.000

0.450

0.540

0.085

0.266

1.000

0.086

33.12-33.12

0.147

29.09-35.11

29.81-32.85

29.81-35.11

29.08-34.16

30.70-32.85

29.08-35.11

35.11-35.11

32.85-34.16

29.08-31.78

29.81-34.16

29.08-32.85

35.11-35.11

29.81-34.16

29.08-35.11

29.09-31.78

30.73-35.11

33.37-33.37

29.08-31.78

29.81-35.11

31.40

31.50

31.78

31.40

31.22

31.59

35.11

33.37

30.73

31.59

30.97

35.11

31.40

32.03

30.70

32.85

33.37

30.96

32.13

33.37

32.08(±2.17)

31.41(±1.26)

32.12(±2.37)

31.68(±1.68)

31.59(±1.12)

31.93(±2.12)

35.11(±n/a)

33.46(±0.66)

30.67(±0.94)

31.87(±1.63)

30.97(±1.55)

35.11(±n/a)

31.71(±1.43)

32.06(±2.69)

30.52(±1.08)

32.85(±1.83)

33.37(±n/a)

30.69(±1.16)

32.34(±2.06)

33.37(±n/a)

0.705

1.000

0.683

0.026*

0.212

1.000

0.086

33.37-33.37

0.266

28.87-35.14

30.45-32.42

30.45-35.14

28.87-33.26

31.18-32.42

28.87-35.14

35.14-35.14

32.42-33.26

28.87-31.96

30.45-33.26

28.87-32.42

35.14-35.14

30.45-33.26

28.87-35.14

28.87-31.96

30.94-35.14

32.75-32.75

28.87-31.96

30.45-35.14

31.96

31.06

32.19

31.18

31.96

31.09

35.14

32.75

30.95

31.46

31.20

35.14

31.18

32.36

30.95

32.42

32.75

31.06

31.82

32.75

32.02(±1.98)

31.25(±0.84)

32.50(±1.96)

31.31(±1.42)

31.86(±0.63)

31.70(±1.94)

35.14(±n/a)

32.81(±0.42)

30.80(±0.96)

31.72(±1.12)

30.92(±1.49)

35.14(±n/a)

31.49(±0.98)

32.18(±2.59)

30.68(±1.15)

32.60(±1.70)

32.75(±n/a)

30.74(±1.32)

32.75(±1.75)

32.75(±n/a)

0.345

0.450

0.683

0.026*

0.266

0.450

0.124

32.75-32.75

0.337

98

Table 24 Continued: Summary of Spatiotemporal Measures Results for "No Aid" Group (significant findings indicated with an asterisk; unable to calculate (utc)) STRATIFICATION RESULTS FOR “NO AID” GROUP Measure n Temp St Sym Range

Median Mean (±SD)

Etiology NTiSCI TiSCI 7 4

Median Mean (±SD)

Median Mean (±SD)

Median Mean (±SD)

Median Mean (±SD)

Median Mean (±SD)

Median Mean (±SD)

Median Mean (±SD) p value

Asym 4

Temp. Variability Groups Low Mod. High 5 5 1

Spatial Variability Groups Low Mod. High 4 6 1

1.12-1.12

1.01-1.05

1.00-1.07

1.00-1.07

1.01-1.12

1.00-1.07

1.01-1.12

1.01-1.01

1.00-1.07

1.01-1.12

1.01-1.01

1.04

1.04

1.04

1.04

1.05

1.04

1.12

1.04

1.04

1.04

1.04

1.04

1.05

1.01

1.04

1.04

1.01

1.04(±0.03)

1.05(±0.05)

1.04(±0.03)

1.04(±0.03)

1.04(±0.04)

1.12(±n/a)

1.03(±0.02)

1.04(±0.03)

1.04(±0.02)

1.05(±0.06)

1.04(±0.03)

1.06(±0.04)

1.01(±n/a)

1.04(±0.04)

1.05(±0.04)

1.01(±n/a)

1.05(±0.04)

0.705 1.01-1.36

0.850

1.02-1.12

1.01-1.36

1.000

1.01-1.12

1.01-1.12

0.285

1.01-1.36

1.36-1.36

1.02-1.10

0.705 1.01-1.12

1.01-1.12

0.441

1.01-1.36

1.02-1.12

1.01-1.36

0.525 1.02-1.02

1.01-1.12

1.01-1.35

1.02-1.02

1.05

1.06

1.06

1.05

1.10

1.04

1.36

1.05

1.02

1.05

1.07

1.02

1.07

1.02

1.07

1.06

1.02

1.09(±0.12)

1.07(±0.05)

1.12(±0.16)

1.06(±0.04)

1.08(±0.06)

1.08(±0.12)

1.36(±n/a)

1.06(±0.04)

1.05(±0.05)

1.06(±0.04)

1.13(±0.16)

1.06(±0.05)

1.12(±0.14)

1.02(±n/a)

1.07(±0.06)

1.10(±0.13)

1.02(±n/a)

1.55-1.55

1.01-1.15

1.01-1.18

1.03-1.18

1.01-1.18

1.02-1.55

1.01-1.01

1.01-1.18

1.02-1.55

0.571 1.01-1.55

0.850

1.03-1.18

1.01-1.55

0.683

1.01-1.18

1.01-1.18

0.285

1.01-1.55

0.850

0.612

1.01-1.55

0.630 1.01-1.01

1.09

1.10

1.10

1.09

1.15

1.08

1.55

1.09

1.06

1.09

1.09

1.06

1.13

1.01

1.10

1.11

1.01

1.14(±0.19)

1.10(±0.07)

1.19(±0.25)

1.09(±0.07)

1.11(±0.09)

1.13(±0.18)

1.55(±n/a)

1.08(±0.07)

1.09(±0.07)

1.09(±0.06)

1.18(±0.25)

1.09(±0.08)

1.19(±0.21)

0.01(±n/a)

1.10(±0.09)

1.17(±0.19)

0.01(±n/a)

0.571

0.850

0.838

0.285

0.850

0.382

0.428

1.01-1.27

1.00-1.10

1.01-1.27

1.00-1.22

1.01-1.14

1.00-1.27

1.27-1.27

1.01-1.13

1.00-1.22

1.00-1.14

1.01-1.22

1.27-1.27

1.00-.122

1.01-1.27

1.13-1.13

1.00-1.22

1.01-1.27

1.13-1.13

1.13

1.02

1.08

1.03

1.10

1.03

1.27

1.02

1.03

1.02

1.06

1.27

1.10

1.02

1.13

1.12

1.02

1.13

1.12(±0.10)

1.03(±0.04)

1.11(±0.12)

1.07(±0.08)

1.08(±0.07)

1.09(±0.11)

1.27(±n/a)

1.05(±0.07)

1.07(±0.08)

1.05(±0.06)

1.09(±0.10)

1.27(±n/a)

1.10(±0.09)

1.07(±0.12)

1.13(±n/a)

1.12(±0.09)

1.06(±0.10)

1.13(±n/a)

0.131 2.11-9.08

0.450

3.79-6.18

4.62-8.53

0.838

2.11-9.08

3.79-6.18

0.273

2.11-9.08

8.53-8.53

5.53-9.08

0.212 2.11-7.62

4.62-9.08

2.11-6.97

0.695 8.53-8.53

3.79-7.62

0.623

2.11-9.08

2.11-5.58

4.93-8.53

9.08-9.08

6.97

5.25

5.55

5.58

4.62

6.27

8.53

6.18

4.93

5.55

4.98

8.53

5.58

6.57

4.20

6.57

9.08

6.35(±2.45)

5.12(±1.02)

6.06(±1.78)

5.51(±2.36)

4.86(±1.22)

6.29(±2.25)

8.53(±n/a)

6.93(±1.89)

5.09(±1.87)

6.23(±1.75)

4.76(±2.23)

8.53(±n/a)

5.80(±1.28)

6.08(±3.32)

4.02(±1.47)

6.63(±1.34)

9.08(±n/a)

0.345

1.000

0.221

0.196

0.311

0.850

0.043*

3.11-12.27

3.33-6.52

3.67-6.52

3.11-12.27

3.67-6.52

3.11-12.27

5.44-5.44

6.52-12.27

3.11-6.12

3.33-12.27

3.11-6.52

5.44-5.44

3.33-6.58

3.11-12.27

3.11-6.12

4.70-6.58

12.27-12.27

5.44

5.41

5.07

5.74

6.12

5.38

5.44

6.58

4.70

5.01

5.93

5.44

5.74

4.55

3.50

5.59

12.27

6.02(±3.01)

5.17(±1.45)

5.08(±1.20)

6.07(±3.04)

5.44(±1.54)

5.81(±2.86)

5.44(±n/a)

8.45(±3.30)

4.57(±1.21)

5.98(±3.30)

5.37(±1.54)

5.44(±n/a)

5.47(±1.16)

6.12(±4.22)

4.06(±1.39)

5.72(±0.73)

12.27(±n/a)

0.850 2.27-15.97

0.705

2.71-8.54

2.59-9.66

0.683

2.27-15.97

2.59-8.54

0.044*

2.27-15.97

9.66-9.66

7.15-15.97

0.981 2.27-7.40

2.59-15.97

2.27-8.54

0.571 9.66-9.66

2.71-8.54

0.085

2.27-15.97

2.27-7.11

7.15-9.66

15.97-15.97

7.26

5.30

7.82

7.15

3.49

7.20

9.66

8.54

3.49

7.13

5.44

9.66

7.15

6.12

2.71

7.40

15.97

7.47(±4.62)

5.46(±2.81)

6.97(±3.10)

6.61(±4.70)

4.87(±3.21)

7.44(±4.26)

9.66(±n/a)

10.55(±4.75)

4.69(±2.43)

7.13(±4.87)

5.42(±3.02)

9.66(±n/a)

6.24(±2.21)

7.62(±6.53)

3.63(±1.99)

8.00(±1.08)

15.97(±n/a)

p value Rt. Spat Var %CV: Range

Symm 7

1.00-1.12

p value Lt. Spat Var %CV: Range

Spat. Symm Groups

1.01-1.07

p value Rt. Temp Var %cv: Range

Temp. Symmetry Groups Symm Asym Sev Asym 6 4 1

1.00-1.07

p value Lt. Temp Var %cv: Range

Velocity Groups Sv Mv 3 7

1.01-1.12

p value Spat. Stp Sym Range

VSv 1

1.00-1.07

p value Tot Temp Sym Range

Severity of Injury AIS C AIS D 3 8

1.01-1.12

p value Temp Sw Sym Range

Level of Injury Tetra Para 4 7

0.571 1.71-12.05

0.705

2.09-6.18

1.71-8.55

0.540

2.09-12.05

1.71-6.18

0.072

2.09-12.05

8.55-8.55

6.18-12.05

0.448 1.71-8.54

1.71-12.05

2.35-8.54

1.000 8.55

2.09-8.54

0.017*

1.71-12.05

1.71-5.08

6.18-8.55

12.05-12.05

6.59

3.73

5.63

6.52

2.38

6.55

8.55

6.59

2.38

5.80

4.28

8.55

6.18

5.45

2.35

6.59

12.05

6.62(±3.63)

3.93(±2.01)

5.38(±2.84)

5.79(±3.77)

3.43(±2.41)

6.47(±3.33)

8.55(±n/a)

8.27(±3.28)

4.10(±2.65)

5.67(±3.77)

4.87(±3.04)

8.55(±n/a)

5.34(±2.36)

6.17(±4.99)

2.72(±1.34)

7.28(±1.17)

12.05(±n/a)

0.186

0.705

0.153

0.105

0.448

0.850

0.017*

99

100

Table 25: Correlations between Spatiotemporal Parameters for the "No Aid" Group PARAMETER Velocity Cadence

Cadence 0.800**

Stance %GC L R -0.364

-0.064

-0.091

-0.273

Swing %GC L R 0.364

0.064

SS %GC L R -0.036

DS %GC L R

Temp. St. Symm

Temp Sw. Symm

Tot. Temp Symm

Spat Symm

0.445

-0.655*

-0.718*

-0.564

-0.518

-0.482

-0.445

-0.400

-0.482

-0.409

0.091

0.273

0.182

0.200

-0.555

-0.709*

Lt Stance %GC

-1.000**

0.745**

0.845**

-0.945**

0.582

0.527

Rt Stance %GC

0.745**

-1.000**

-0.973**

0.555

-0.036

-0.173

Lt Swing %GC

-0.845**

0.945**

-0.582

-0.527

-0.055

Rt Swing %GC

0.973**

-0.555

0.036

0.173

0.802

0.155

0.255

0.082

0.127

0.109

-0.764**

-0.618*

0.055

-0.073

-0.036

Left DS %GC

0.018

0.164

Right DS %GC

0.100

0.200

Temp Var %CV L R -0.418

-0.700*

Spat Var %CV L R -0.673*

-0.691*

-0.227

-0.036

-0.673*

-0.336

-0.273

0.136

-0.118

0.809**

0.364

0.809**

0.618*

-0.045

-0.091

-0.427

0.173

-0.373

-0.218

0.118

-0.809**

-0.364

-0.809**

-0.618*

0.091

0.427

-0.173

0.373

0.218

0.055

0.500

-0.082

0.455

0.273

0.182

-0.873**

-0.418

-0.818**

-0.618*

0.118

-0.127

0.682*

0.645*

0.700*

0.627*

0.091

0.227

0.527

0.691*

0.645*

0.582

0.518

-0.127

0.109

0.145

0.291

Temp Sw. Symm

0.400

-0.191

0.091

0.055

0.109

Tot Temp Symm

0.318

-0.173

0.073

0.082

0.155

-0.127

-0.073

Left SS %GC Right SS %GC

Temp St. Symm

Spatial Symm

0.864**

-0.009

0.127

Lt Temp Var %CV

0.891**

0.800**

Rt Temp Var %CV

0.745**

0.718*

* Correlation is significant at the 0.05 level (2-tailed) **Correlation is significant at the 0.01 level (2-tailed)

101

102 8.2.5

Results for Velocity Groups

103 Table 26: Summary of Clinical Measures Results for Velocity Groups (significant findings indicated with an asterisk*)

VELOCITY GROUP Measure LEMS

n Range Median Mean (±SD) p value Base 10mWT n Range Median Mean (±SD) p value p value EXT SLOW p value VERY SLOW p value SLOW Base 6MWT n Range Median Mean (±SD) p value p value EXT SLOW p value VERY SLOW p value SLOW Base TUG Range n Median Mean (±SD) p value p value EXT SLOW p value VERY SLOW p value SLOW Base ADS n Range Median Mean (±SD) p value Base WISCI n Range Median Mean (±SD) p value Adm FIM n Range Median Mean (±SD) p value Base WMS n Range Median Mean (±SD) p value

ESv

VSv

Sv

Mv

(