without a Front-Wheeled Rolling Walker Independent Research Presented to The Faculty of the Department of Physical Therapy

The Analysis of Gait Kinematics of Participants in the Subacute Phase of Stroke with and without a Front-Wheeled Rolling Walker Independent Research Presented to The Faculty of the Department of Physical Therapy Florida Gulf Coast University In Partial Fulfillment Of the Requirement for the Degree of Doctorate of Physical Therapy By Lucas D Egan 2014

APPROVAL SHEET This independent research is submitted in partial fulfillment of the requirements for the degree of Doctorate of Physical Therapy Approved: December 2014 Lucas D Egan Dr. Mollie Venglar, DSC, MSPT, NCS Dr. Arie van Duijn, EdD, PT, OCS Dr. Jacqueline van Duijn, DPT, OCS, DCE The final copy of this independent research has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline.

Acknowledgements I would like to thank several people in the their assistance of helping me achieve the completion of this research study. First, I would I would like to thank my awesome and knowledgeable research committee, specifically Dr. Mollie Venglar, Dr. Arie Van Duijn, and Dr. Jacqueline Van Duijn for their patience and guidance through the finalizing and this research study. Also, I would like to thank NCH Brookdale Center for Healthy Aging and Rehabilitation and the participants for allowing me the opportunity to perform this study and share in the knowledge of stroke rehabilitation. A significant amount of gratitude goes to Dr. Derek Lura helping me learn how to use the Qualysis and Visual 3D programs. I know it took a lot of time and patience, so thank you for not giving up on me. Lastly, I would like to thank my friends and family for being with me through this process. You all have provided me the love and support that cannot be measured through a research study that has allowed me to reach my goals in life. I cannot thank everyone enough who has helped me through this process.

Running Head: Analysis of Gait Kinematics 4 Table of Contents Acknowledgements... 3 Abstract... 5 Introduction... 6 Stroke Overview... 6 Fear of Falling Effect on Gait... 8 Gait Kinematics in Stroke... 9 Gait Kinematics with an Assistive Device... 10 Research Question... 14 Hypothesis... 14 Methods... 14 On- Going Study... 15 Qualisys and Visual 3D... 15 Data analysis... 16 Results... 17 Participant 1... 17 Participant 2... 17 Participant 3... 18 Participant 4... 18 Participant 5... 18 Table 1. Comparison of Means Without and With a Front- Wheeled Rolling Walker... 19 Discussion... 20 References... 23

Analysis of Gait Kinematics 5 Abstract Background: There is limited research on how assistive devices affect the gait kinematics of people in the subacute phase of stroke. The effects of walking with and without a frontwheeled rolling walker on the gait kinematics of participants in the subacute phase of stroke has not been examined. Methods: 5 participants walked with and without a front-wheeled rolling walker while a Qualysis camera system captured kinematic data. The Qualisys system integrates the individual camera data and converts this into real time motion data. Specifically, step length, step width, stride length, peak knee flexion, peak hip flexion, trunk rotation, and trunk flexion were assessed. The participants were categorized into 5 individual case studies. The data was analyzed using multivariate and univariate analysis. Both the univariate and multivariate analysis compared the means of dependent variables with and without a walker. Results: Each participant demonstrated differences in gait patterns with and without the front wheeled rolling walker unique to that participant. Step width was not changed among the subjects. The data had a significant difference if the p-value was less than.05. Discussion: Participants 1, 2, and 5 showed either improved step length, stride length, peak knee flexion, or peak hip flexion gait kinematics when walking without a front-wheeled rolling walker. Participants 3 and 4 had improved gait mechanics when using a front-wheeled rolling walker. The changes in participants gait kinematics with and without a front-wheeled rolling walker demonstrates that more research needs to be performed in this area. Future studies should look at the difference in gait kinematics when using other assistive devices, such as a 4-wheeled walker or loft strand crutches, among participants in the subacute phase of stroke.

Analysis of Gait Kinematics 6 Introduction Each year 750,000 people in the United States are diagnosed with having a stroke. Approximately 81% of the strokes diagnosed per year occur to people experiencing their first stroke. Americans paid over 70 billion dollars in 2010 for medical cost due to a stroke (Go, Mozaffarian, Roger, Benjamin, & Berry, 2013). Stroke Overview A stroke is caused by lack of blood flow to the brain. 87% of strokes are classified as ischemic and 13% are classified as hemorrhagic (Go et al., 2013). Ischemic stroke occurs when an embolus or thrombus occludes an artery supplying oxygen to the brain. The clot can be caused by narrowing of the blood vessel (thrombic) or when a clot breaks off from a blood vessel within the body and lodges in a blood vessel in the brain (embolic). Hemorrhagic stroke occurs when a weakened blood vessel ruptures and blood accumulates around the brain. The 2 types of hemorrhagic stroke are intracerebral and subarachnoid hemorrhage. The two greatest causes of these are aneurysms and arteriovenous malformations. When the brain is deprived of oxygen it causes necrosis of neurons, which can lead to permanent brain damage. Neurons have an extremely limited ability to heal after damage, thus the damage can be permanent. These neuronal connections are necessary for the body to send and receive signals from the brain for various functions such as walking, sensation, and proprioception. The symptoms of stroke can be subtle at first but they become more evident as time goes on (Zieve & Jasmin, 2010). The initial symptoms of stroke are sudden numbness or weakness of the leg and arm, sudden confusion, trouble seeing in one or both eyes, trouble walking, dizziness, loss of balance or coordination, facial droop to one side, or a severe headache with no known cause. The effects of stroke can decrease gait performance through muscular,

Analysis of Gait Kinematics 7 physiological, and psychological factors. The muscular factors effecting gait are loss of muscle control, ataxia, increased or decreased muscle tone, and dyspraxia. The physiological factors are altered sensation on one side of the body, inattention or neglect of part of the body, pain, vision problems, fatigue, dizziness, and side effect of medicine. The psychological factors are poor concentration, fear of falling, and motivation (Effects of stroke which may make balancing and regaining mobility difficult.2013; O'Sullivan & Schmidtz, 2007). The frontal lobe of the brain, basal nuclei, and the cerebellum are responsible for the process of gait. The frontal lobe parts can be broken down into 3 parts, which are the primary motor cortex, premotor cortex, and prefrontal cortex. The primary motor cortex is responsible for the control of voluntary movement. The premotor cortex, also known as the somatic motor association area, is used for more complex movements such as making a fist with one hand and putting the palm down on the other. The prefrontal cortex functions to integrate sensory information with appropriate motor responses (Schenkman, Bowman, Gisbert, & Butler, 2013). Other areas of the brain, the basal nuclei, and the cerebellum influence movement as well. The basal nuclei play an important role in maintaining posture and movement. They function to initiate movement, regulate movement, plan and execute complex movements, inhibit unwanted movements, and perform postural adjustments (Schenkman et al., 2013). The cerebellum helps to keep coordination during movement and continues movement unconsciously such as walking while talking (Schenkman et al., 2013). The areas of the brain that are responsible for movement are supplied by different blood vessels. The frontal lobe is supplied by the middle cerebral artery (MCA), anterior cerebral artery (ACA), pericallosal, and callosomarginal. The basal nuclei are supplied by the

Analysis of Gait Kinematics 8 lateral striate artery from the MCA, anterior choroidal artery from the internal carotid, and the medial striate artery from the ACA. The cerebellum is supplied by the posterior inferior cerebellar artery that comes off the vertebral arteries. The anterior inferior cerebellar and superior cerebellar arteries coming off the basilar artery also supply the cerebellum (Schenkman et al., 2013). Treatment for patients post-stroke consists of bed mobility training, sitting balance exercises, transfer training, wheelchair mobility, pre-gait exercises, and balance and gait training. Presently, there is no consensus on the best treatment for patients post-stroke (McCain et al., 2008). Assistive devices may be used for gait training. Assistive devices frequently used for gait training patients after stroke are walkers, canes, or crutches. The assistive devices are designed to improve gait speed, functional tasks, safety, balance, and quality of life (Jette et al., 2005). Fear of Falling Effect on Gait Fear of falling has been reported to have an effect on gait. After having a stroke it can be scary to walk again due to decreased balance and motor control among other factors. A study was performed observing 95 community dwelling adults between the ages of 60-97 (Chamberlin, Fulwider, Sanders, & Medeiros, 2005). They all completed the Modified Falls Efficacy Scale to and all scored in fearful or fearless group. The fearful group demonstrated the most significant gait changes. The participants walked at their normal gait speeds over a GaitRite mat. The fearful group had shorter stride length, prolonged double limb stance time, slower gait speed, and increased step width (Chamberlin et al., 2005). Delabere et al. (2009) assessed 44 community dwelling adults with a mean age of 76.8 years for differences in gait kinematics based upon physiological fall risk and fear of

Analysis of Gait Kinematics 9 falling. Each participant was assessed for physiological fall risk through the Physiological Profile Assessment and fear of falling by the Falls Efficacy Scale International (Delbaere, Sturnieks, Crombez, & Lord, 2009). The participants were instructed to walk at their normal gait speed through four different lighting atmospheres. Temporal and spatial gait data was measured. The results showed that gait kinematics are affected by physiological and psychological factors. The participants who feared falling had slower gait speeds and less trunk rotation (Delbaere et al., 2009). Fear of falling has significant effect of gait kinematics that leads to a tightened trunk, slower gait speed, and shorter step lengths. Gait Kinematics in Stroke There are many types of gait patterns in patients post-stroke. Verma, Arya, Sharma, and Garg (2012) conducted a meta-analysis concentrating on post-stroke gait deviations of patients and the therapeutic interventions used to assist with the gait. Some common signs in post-stroke gait are poor paretic (affected) limb body weight support, unbalanced forward movement, slower gait speed, unequal step lengths, and prolonged swing time. On the nonparetic or unaffected limb, patients often have decreased swing phase and an increased stance phase (Verma, Arya, Sharma, & Garg, 2012). These gait deviations have led researchers to conduct studies on how walking performance differs between people post-stroke and those who have not had a stroke. Chen, Patten, Kothari, and Zajac (2005) performed a study of six individuals with post-stroke hemiparesis and six control participants without any occurrence of a stroke (Chen, Patten, Kothari, & Zajac, 2005). Each participant post-stroke was paired up with a non-stroke participant and walked on two separate treadmills, set at matched walking speeds. Pedar insole pressure sensors were put in the shoes of each participant to record foot pressure.

Analysis of Gait Kinematics 10 Isokinetic knee extension torque was measured by the use of a dynamometer for each participant to compare lower extremity strength. It was determined from the study that the post-stroke participants had difficulty with swing-initiation while walking on the treadmill and decreased leg propulsion power (Chen et al., 2005). Another study was performed observing one participant with hemiparesis and one healthy control. In this study, both of the participants walked on a treadmill at 0.75 m/s while the researchers collected data on kinematic, kinetic, real-time muscle fascicle image, and carbon dioxide flow rate (Hampton, Farris, & Sawicki, 2009). A visual 3-D system was used to gain kinematic data. The study s results showed that the participant post-stroke used almost double the net metabolic walking power of that of the healthy control. Also, the participant post-stroke had more joint positive mechanical work during gait. This was due to increased total workload of the lower extremity and redistribution of work to proximal muscle tendon units (Hampton et al., 2009). Gait Kinematics with an Assistive Device Van Hook, Demonbreun, and Weiss state in their study that front-wheeled walkers are used when patients gait is too fast for a standard walker or when the patients are unable to lift a standard walker (2003). They also report that front-wheeled walkers can be used to help with ambulation in patients with frontal lobe gait disorders (Van Hook, Demonbreun, & Weiss, 2003). A study conducted by Liu, Mcgee, Wang, and Womack assessed the effects of the use of a front-wheeled rolling walker on gait (2011). In this study, there were three groups consisting of one group of elderly participants using a rolling walker for household ambulation, one group of elderly participants using a walker for community gait, and one

Analysis of Gait Kinematics 11 group of college students with an unremarkable history in the last 12 months not using a walker. The authors reported that the rolling walker did not disrupt the subjects gait pattern but did enhance a forward trunk lean on the walker (Liu, Mcgee, Wang, & Womack, 2011). No studies have been identified comparing gait kinematics with and without a walker post-stroke; however, studies have been conducted for participants with Parkinson s disease, Huntington s disease, Spina Bifida, and spinal cord injury. The gait kinematics of participants with Parkinson s disease was examined. This was done both with and without an assistive device (Liu, McGee, Wang, & Persson, 2009). The participants were divided into two groups: those who used a rolling walker for ambulation and those who did not use a rolling walker for ambulation. The participants in both groups walked on a GAITRite mat with and without the rolling walker three times each. The group that used a rolling walker for ambulation prior to the study exhibited decreased cadence, swing, speed, step length, and stride length when walking independently compared to the other group. Using the rolling walker increased double limb support and stance time compared to not using the walker. The observed gait pattern with the rolling walker for both groups included smaller step length, slower gait speed, increased stance time, and decreased swing time. The results indicated that the gait pattern might become more exaggerated when the participant uses the rolling walker for long-term usage (Liu et al., 2009). This is the result of three different factors. First, bilateral somatosensory input might be adapted to quadrilateral somatosensory inputs from both upper extremities (UE) and lower extremities (LE) with long-term use of a rolling walker. This would lead to altered static and dynamic balance due to poor LE somatosensory input when a rolling walker is not available, which can lead to falls. Second, using a rolling walker shifts the center of gravity more superiorly

Analysis of Gait Kinematics 12 and anteriorly resulting in possible postural changes in longer term rolling walker users. Third, rolling walkers allow the UEs to compensate for weak LE muscles by allowing the UE to bear body weight through the rolling walker. This can lead to decreased LE weight loading, which can lead to increased LE weakness (Liu et al., 2009). Kegelmeyer et al, assessed the effects assistive devices had on participants with Parkinson s disease and the results differed from the study by Liu et al (2009). In this study 27 participants with Parkinson s disease were examined for their gait kinematics both with and without a walker (Kegelmeyer, Parthasarathy, Kostyk, White, & Kloos, 2013). The participants walked on a GAITRite mat in a figure 8 pattern, both with and without assistive devices. The assistive devices used were canes, standard and wheeled walkers. All the devices, except the four-wheeled walker, decreased the gait speed during ambulation. The four-wheeled walker showed the least variability among the assistive devices and was the best at eliminating compensatory gait patterns. The four-wheeled walker increased gait speed, step length, and there was more time spent in swing phase than in double limb support during the gait cycle. These results were consistent throughout the data collection (Kegelmeyer et al., 2013). The four-wheeled walker was the best device in this study for improving gait, decreasing compensation patterns, and safety. Kloos, Kegelmeyer, White, and Kostyk examined participants with Huntington s disease and their gait kinematics (2012). The 21 participants with Huntington s disease walked on a GaitRite walkway through seven different conditions. Step length, gait speed, double limb support time, swing time, and step variability data was retrieved during these trials. Canes, 2-wheeled, 3-wheeled and 4-wheeled walkers were used during the trials. Gait safety and variability was best when using a 4-wheeled walker, especially when compared to

Analysis of Gait Kinematics 13 the other assistive devices. All assistive devices decreased gait speed when compared to not using the assistive device during all seven of the conditions (Kloos, Kegelmeyer, White, & Kostyk, 2012). However, the participants gait speed was the fastest when using the 4- wheeled walker when compared to the other assistive devices. A study of gait kinematics when using assistive devices was performed with participants with spina bifida and spinal cord injury (Johnson, Fatone, & Gard, 2009). The participants gait kinematics, when using assistive devices, were measured using a 3-D motion analysis system. The assistive devices used were parallel bars, crutches and an anterior rolling walker. The results of the study revealed that all of the participants walked with a flexed trunk. They also bore a large percentage of their body weight through the upper extremities while in single leg stance. Trunk extension was observed when the shoulders took upon most of the participant s weight, but trunk flexion was observed when the hips bore most of the weight. This relationship was consistent throughout all of the assistive devices. Research is lacking comparing the gait kinematics of participants post-stroke both with and without a walker. The studies discussed here are the only studies available that may show similar results for participants post-stroke. These studies involve participants with Parkinson s disease, Huntington s disease, Spina Bifida, and spinal cord injury. These groups may show similar gait kinematics when compared to participants post-stroke, although the data cannot be generalized to participants post-stroke because the brain is affected differently or the spinal cord is affected.

Analysis of Gait Kinematics 14 Research Question Is there a difference in the gait speed, step length, step width, peak knee flexion moments, peak hip flexion moments, trunk rotation moments, and trunk flexion moments of participants in the subacute stroke phase with and without the use of a front-wheeled rolling walker as measured by Qualisys and analyzed through Visual 3D? Hypothesis The hypothesis for the study is that there will be a significant difference in the gait kinematics of participants in the subacute stroke phase with and without the use of a frontwheeled rolling walker. The participants using a rolling walker will have increased peak hip flexion, step length, peak knee flexion, trunk flexion, and decreased step width. The center of gravity is anticipated to be translated forward due to leaning forward on the walker. Methods This is a retrospective study of data previously collected. The dependent variables in this study are step length, stride length, step width, peak knee flexion moments, peak hip flexion moments, and trunk moments. The independent variable is the use of a front-wheeled rolling walker. The participants signed informed consent forms and were recruited using purposive sampling. All of the participants came from the NCH Brookdale Center for Healthy Aging and Rehabilitation (Brookdale). The inclusion criteria were: current in-patient at Brookdale, unilateral stroke affecting at least the lower limb, and medically stable as determined by Brookdale. Exclusion criteria included: previous stroke with residual lower limb deficit, and any lower extremity pathology on the affected side other than the effects of the stroke. IRB approval was obtained.

Analysis of Gait Kinematics 15 On-Going Study The research questions of the prior study are: Will people with stroke who are trained with body weight support (BWS) show better gait kinematics than those trained without BWS?, and How closely will the gait kinematics of both groups resemble normal gait kinematics of an age-matched population without stroke?. The design of the project is a randomized controlled trial, utilizing patients post stroke currently admitted and treated at Brookdale. The control group receives traditional gait training; the experimental group receives BWS. Gait at discharge from Brookdale is analyzed via motion analysis. Groups are compared to each other and to a normative data set of age-matched individuals without stroke. In the ongoing study, investigators placed reflective markers bilaterally on the following areas using non-latex adhesive tape: top of both acromions, on the PSIS and ASIS, greater trochanter, group of markers on the quadriceps muscles and lower leg, lateral and medial epicondyle of the femur, tibialis anterior, lateral and medial malleolous, first and fifth metatarsals, and on the calcaneus. Markers were placed on the walker at the bottom of the front legs and the handles. Each participant walked across the room up to ten times both with and without a front-wheeled rolling walker, while gait parameters and kinematics were recorded. All participants walked first with the walker, then without the walker. The participants were allowed rest during the trials. Qualisys and Visual 3D The Qualisys system works by using infrared cameras to send infrared light. The cameras also capture the infrared light at a frequency of 33kHz coming back from the reflective markers. The Qualisys system integrates the individual camera data and converts this into

Analysis of Gait Kinematics 16 real time motion data (C-motion research biomechanics, 2013). This data can consist of joint moments, gait speed, step length, step width, stance phase, and swing phase among variables. Qualisys allows any marker set to be used by the researcher. Data from Qualisys is easily transferable to Visual 3D. Visual 3D and Qualisys have the same type of file format (C3D), which makes transferring data simple and does not change any of the data already recorded. The Visual 3D system uses the recorded marker set to make a skeletal model of the participant (Gait analysis and rehabilitation, 2013). This study used a hybrid model and a Helen Hayes marker set to define the pelvis. Joint angles can be calculated on Visual 3D based on rotations between segments defined in the model. The center of mass can be approximated given the position of all of the body segments the mass properties are assumed, but the accuracy is limited. Data analysis The data from the study compared step length, step width, stride length, peak knee flexion moments, peak hip flexion moments, trunk rotation, and trunk flexion of participants walking with and without a front-wheeled rolling walker. The trunk rotation and flexion were analyzed by the position of the acromion relative to the ASIS during the gait cycle. Mathematical formulas within the data pipeline were created to achieve data for the dependent variables. Step and stride length were collected every time a heel strike occurred. Peak hip and knee flexion moments were collected during the gait cycle of each trial. The data was recorded using the 3-D motion analysis system and Visual 3D. The data was analyzed using an IBM SPSS statistics GRAD PACK 22.0 base program. The participants were categorized into 5 individual case studies. For participants 1 and 2 a univariate analysis was used for step length, step width, right stride length, and left stride length. A multivariate

Analysis of Gait Kinematics 17 analysis was used for peak right knee flexion, peak left knee flexion, peak right hip flexion, peak left hip flexion, trunk rotation, and trunk flexion. Participants 3, 4, and 5 had a univariate analysis used on all dependent variables. Both the univariate and multivariate analysis compared the means of dependent variables with and without a walker. The data had a significant difference if the p-value was less than.05. Results Participant 1 Participant 1 is a 65-year-old female with a right cerebrovascular accident. The participant received traditional gait training. There were 5 trials conducted with a frontwheeled rolling walker and 5 trials without the assistive device. The participant had significant differences for peak R knee flexion, peak L knee flexion, peak L hip flexion, trunk rotation, and trunk flexion (Table 1). Without the use of a front-wheeled rolling walker participant 1 had 1.69 more degrees peak R knee flexion (N=10) (p<.001), 1.76 more peak L knee flexion (N=10) (p<.001), 1.74 more peak L hip flexion (N=10) (p=.043), 7.72 more trunk flexion (N=10) (p<.001), and 2.4 less trunk rotation (N=10) (p=.022). Participant 2 Participant 2 is a 78-year-old male with a left cerebrovascular accident. The participant received traditional gait training. There were 4 trials conducted with a front-wheeled rolling walker and 4 trials without the assistive device. The participant had significant differences for step length, R and L stride length, peak R hip flexion, and trunk flexion (Table 1). Without the use of a front-wheeled rolling walker participant 2 had.1079 more meters of step length (N=26) (p=.001), 0.2741 more meters of stride length R (N=27) (p<.001), 0.1655 more meters of stride length L (N=26) (p<.001), and 10.96 less R hip flexion (N=8)

Analysis of Gait Kinematics 18 (p=.017). Participant 2 almost had significant differences for peak L hip flexion (N=8) (p=.069) and trunk flexion (N=8) (p=.068). Participant 3 Participant 3 is a 65-year-old male with a right cerebrovascular accident. The participant received traditional gait training. There were 7 trials conducted with a frontwheeled rolling walker and 3 trials without the assistive device. The participant had significant differences for R and L stride length, peak R knee flexion, peak R hip flexion, trunk rotation, and trunk flexion (Table 1). Without the use of a front-wheeled rolling walker participant 3 had 0.2626 less meters of stride length R (N=57) (p<.001), 0.254 less meters of stride length L (N=57) (p<.001), 3.22 less peak R knee flexion (N=10) (p=.031), 5.76 more peak R hip flexion (N=10) (p=.006), 3.32 more trunk rotation (N=10) (p=.036), and 13.61 more trunk flexion (N=10) (p<.001). Participant 4 There were 5 trials conducted with a front-wheeled rolling walker and 4 trials without the assistive device. The participant had significant differences for step length and trunk rotation (Table 1). Without the use of a front-wheeled rolling walker participant 4 had.0519 less meters of step length (N=42) (p=.020) and 2.89 more trunk rotation (N=9) (p=.016). Participant 5 Participant 5 is a 43-year-old male with a left cerebrovascular accident. The participant received BWS gait training. There were 5 trials conducted with a front-wheeled rolling walker and 4 trials without the assistive device. The participant had significant differences for stride length L, peak L hip flexion, and trunk rotation (Table 1). Without the use of a front-wheeled rolling walker participant 5 had.0548 more meters of stride length L (N=41)

Analysis of Gait Kinematics 19 (p=.026), 2.36 more L hip flexion (N=9) (p<.001), and 2.91 more trunk rotation (N=9) (p=.025). Table 1. Comparison of Means Without and With a Front-Wheeled Rolling Walker Participant Step Length (m) 1.3891.3869 2 *.5211 *.4132 3.3706.3608 4 *.5186 *.5705 5.4062.3881 Step Width (m).0024.0029.0035.0050.0010.0034.0010.0110.0195.0232 Stride length R (m).7655.7778 *1.031 *.7569 *.4613 *.7249.9926 1.029.8271.7929 Stride length L (m).7613.7745 *1.035 *.8695 *.4848 *.7388 1.013 1.024 *.8308 *.7760 Peak R knee flex (deg) *46.45 *44.76 72.72 66.88 *43.32 *46.44 48.63 42.76 55.53 53.85 Peak L knee flex (deg) *13.85 *12.09 13.97 18.06 24.66 23.31 23.55 22.11 38.67 39.39 Peak R hip flex (deg) 16.96 16.02 *7.15 *18.11 *12.47 *6.71 14.55 11.13 16.45 15.31 Peak L hip flex (deg) *14.44 *12.70 2.50 7.90 11.20 8.61 19.27 18.38 *20.24 *22.60 Trunk Rotation (deg) *13.78 *16.18 10.05 11.33 *18.42 *15.10 *11.24 *8.35 *9.60 *12.51 * signifies p-value less than.05 The top number is without a walker and the bottom number is with a walker Trunk Flexion (deg) *31.63 *23.91 10.49 8.09 *20.30 *6.69 8.60 9.20 7.85 6.96

Analysis of Gait Kinematics 20 Discussion The results from the data varied for each participant. The only common occurrence within all of the participants was that walking with and without a front wheeled rolling walker did not result in a significant difference in step width. The type of treatment received did not have a significant impact on the kinematic data. It was thought that walking with an assistive device would decrease the step width due to the improved base of support when using the front-wheeled walker. The assistive device did not impact significantly decreasing or increasing step width. Participants 1, 2, and 5 showed improved gait kinematics without the front-wheeled rolling walker. More specifically the participants 1,2, and 5 had either improved step length, stride length, peak knee flexion, or peak hip flexion gait kinematics when walking without a front-wheeled rolling walker. These results of this study were the same as the study by Liu et al (2009). The participants in Liu et al study demonstrated decreased step length, stride length, and increased double limb stance time when using an assistive device. These results were opposite of what was hypothesized as the effects of using a rolling walker for this study. The front-wheeled rolling walker could have acted like an obstacle for these participants during the gait trials limiting their ability to walk with a normal gait pattern. Participants 3 and 4 had improved gait mechanics when using an assistive device. This was more evident with participant 3. The largest impact of walking with the front-wheeled rolling walker was improved step and stride length in these subjects. The assistive device allowed for the participants to bear weight through their arms and achieve longer steps. Trunk rotation varied among participants. Participants 1 and 5 showed significantly less trunk rotation when walking without the assistive device as opposed to participants 3 and

Analysis of Gait Kinematics 21 4 who had more trunk rotation with the front-wheeled rolling walker. It was hypothesized that more trunk rotation would occur without the assistive device because arm swing would account for more trunk rotation. Less trunk rotation could have occurred due to fear of falling and the accompanying walking mechanics. Fear of falling can lead to a tightened trunk and less trunk rotation (Chamberlin et al., 2005; Delbaere et al., 2009). It was expected that more trunk flexion would occur when using the front-wheeled rolling walker because of the need to bend over to allow weight to be distributed through the arms. This was not always the case. Participants 1 and 3 had significantly more trunk flexion when walking without the assistive device. The other participants showed no significant differences in trunk flexion when walking with and without the assistive device. The increased trunk flexion with an assistive device could be because the participants had weak back extensors that would not allow them to stand more upright during gait. The assistive device helped these subjects to maintain a more upright posture and increased safety during gait. This study does have limitations. Not all of the participants had an equal number of trials with and without the front-wheeled rolling walker. The data could have also have been impacted by the treatment the participants were receiving (traditional vs. BWSTT), but there was an inadequate number of participants to determine the impact. A pattern was not conclusive between treatment the participants received and impact it had on the dependent variables. The difference in the participants gait kinematic data with and without a frontwheeled rolling walker proves that more research needs to be performed in this area. The results from the study differed from participant to participant except for no significant

Analysis of Gait Kinematics 22 difference with step width for all of the participants. In addition to a large number of participants, future studies should look at the difference in gait kinematics when using other assistive devices, such as a 4-wheeled walker or loft strand crutches, among participants in the subacute phase of stroke.

Analysis of Gait Kinematics 23 References Chamberlin, M. E., Fulwider, B. D., Sanders, S. L., & Medeiros, J. M. (2005). Does fear of falling influence spatial and temporal gait parameters in elderly persons beyond changes associated with normal aging? The Journals of Gerontology.Series A, Biological Sciences and Medical Sciences, 60(9), 1163-1167. Chen, G., Patten, C., Kothari, D. H., & Zajac, F. E. (2005). Gait differences between individuals with post-stroke hemiparesis and non-disabled controls at matched speeds. Gait & Posture, 22(1), 51-56. C-motion research biomechanics. (2013). Retrieved June/18, 2013, from http://www.cmotion.com/products/visual3d/ Delbaere, K., Sturnieks, D. L., Crombez, G., & Lord, S. R. (2009). Concern about falls elicits changes in gait parameters in conditions of postural threat in older people. The Journals of Gerontology.Series A, Biological Sciences and Medical Sciences, 64(2), 237-242. Effects of stroke which may make balancing and regaining mobility difficult. (2013). Retrieved June/18, 2013, from http://www.stroke4carers.org/?p=2298 Gait analysis and rehabilitation. (2013). Retrieved June/18, 2013, from http://www.qualisys.com/applications/biomechanics/gait-analysis-and-rehabilitation/ Go, A., Mozaffarian, D., Roger, V., Benjamin, E., & Berry, J. (2013). Heart disease and stroke Statistics 2013 update: A report from the american heart association. Circulation, 127 Hampton, A., Farris, D., & Sawicki, G. (2009). Mechanics and energetics of post-stroke walking: Towards a muscle- level understanding. Gait & Posture, 8, 1-2. Jette, D. U., Latham, N. K., Smout, R. J., Gassaway, J., Slavin, M. D., & Horn, S. D. (2005). Physical therapy interventions for patients with stroke in inpatient rehabilitation facilities. Physical Therapy, 85(3), 238-248. Johnson, W. B., Fatone, S., & Gard, S. A. (2009). Walking mechanics of persons who use reciprocating gait orthoses. Journal of Rehabilitation Research and Development, 46(3), 435-446. Kegelmeyer, D. A., Parthasarathy, S., Kostyk, S. K., White, S. E., & Kloos, A. D. (2013). Assistive devices alter gait patterns in parkinson disease: Advantages of the fourwheeled walker. Gait & Posture, 38(1), 20-24.

Analysis of Gait Kinematics 24 Kloos, A. D., Kegelmeyer, D. A., White, S. E., & Kostyk, S. K. (2012). The impact of different types of assistive devices on gait measures and safety in huntington's disease. PloS One, 7(2), e30903. Liu, H., Mcgee, M., Wang, W., & Womack, J. (2011). Effects of a forward-leaning posture on gait parameters in individuals using rolling walkers for ambulation assistance. Physical Therapy, 1(4), 1-9. Liu, H. H., McGee, M., Wang, W., & Persson, M. (2009). Comparison of gait characteristics between older rolling walker users and older potential walker users. Archives of Gerontology and Geriatrics, 48(3), 276-280. McCain, K. J., Pollo, F. E., Baum, B. S., Coleman, S. C., Baker, S., & Smith, P. S. (2008). Locomotor treadmill training with partial body-weight support before overground gait in adults with acute stroke: A pilot study. Archives of Physical Medicine and Rehabilitation, 89(4), 684-691. O'Sullivan, S., & Schmidtz, T. (Eds.). (2007). Physical rehabilitation (5th ed.). Philadelphia, PA: F.A. Davis Company. Schenkman, M., Bowman, J., Gisbert, R., & Butler, R. (Eds.). (2013). Clinical neuroscience for rehabilitation. Boston, MA: Pearson. Van Hook, F. W., Demonbreun, D., & Weiss, B. D. (2003). Ambulatory devices for chronic gait disorders in the elderly. American Family Physician, 67(8), 1717-1724. Verma, R., Arya, K. N., Sharma, P., & Garg, R. K. (2012). Understanding gait control in post-stroke: Implications for management. Journal of Bodywork and Movement Therapies, 16(1), 14-21. Zieve, D., & Jasmin, L. (2010). Stroke. Retrieved March/22, 2013, from http://www.ncbi.nlm.nih.gov/pubmedhealth/pmh0001740/