Training functional mobility using a dynamic virtual reality obstacle course

Falling poses a significant risk of injury for older adults, thus decreasing quality of life. Major risk factors for falling include decrements in gait and balance, and adverse patient-reported health and well-being. Virtual Reality (VR) can be a cost-effective, resource-efficient, and highly engaging training tool, and previous research has utilized VR to reduce fall-risk factors in a variety of populations with aging and pathology. However, there are barriers to implementing VR as a training tool to improve functional mobility in older adults that include the manner in which healthy older adults perform in VR relative to younger adults, the effect of extended duration training, and the relation of fall-risk clinical metrics to performance in VR. The purpose of this dissertation is threefold: (1) to compare performance between older and younger adults in VR and in real-world gait and balance tests as a result of a single bout of VR training; (2) to compare performance in VR and gait and balance within younger adults as a result of extended training duration; and (3) to evaluate clinical tests as prerequisite measures for performance within the VR environment. Thirty-five healthy adults participated in this study and were placed into either the older adult training group (n=8; 67.0±4.4yrs), younger training (n=13; 22.1±2.5yrs), or younger control (n=13; 21.7±1.0yrs). All participants completed an online patient-reported survey of balance confidence and health and well-being, as well as a pre-test of clinical assessments and walking and balance tests. The training groups then completed 15 trials of a VR obstacle course, while the controls walked overground for 15 minutes. The VR obstacle course included a series of gait and dynamic balance tasks, such as stepping on irregularly placed virtual stepping stones and walking a virtual balance beam. All participants repeated the walking and balance tests at post-test. The younger training group also completed 3 weeks of training in the same VR obstacle course and a second post-test. Analyses of variance were completed to determine the extent to which participants improved within VR and the walking and balance tests both as a result of a single bout of training, and for the younger adults – three weeks of extended training. Multiple regressions were run to determine the extent to which patient-reports and clinical assessments may predict performance within VR. The results reported in Manuscript I show that although younger adults completed the VR course quicker, their learning rate was not different from older adults; and as a result of extended training, younger adults continued to improve their time to complete the course. For gait and balance tests, age related differences were observed. Both groups showed better performance on some post-tests, indicating that VR training may have had a positive effect on neuromotor control. The results reported in Manuscript II suggest the RAND-1 pain subscale and simple reaction time (SRT) may predict time to complete the VR course, and SRT and BBS Q14 may additionally predict obstacle contact. These data suggest a VR obstacle course may be effective in improving gait and balance in both younger and older adults. It is recommended that future work enroll older adults in the extended training portion of the study and to increase the VR obstacle course difficulty when benchmarks are met

Virtual obstacle crossing and the clinical implications for rehabilitation

Fall risk is a concern for a variety of clinical populations, especially in lower-limb amputees. The risk of falling during walking is increased by an individual with pathology’s diminished ability for obstacle negotiation. Virtual obstacle crossing environments offer a rehabilitation technique that is space and material efficient and may enhance obstacle crossing skill acquisition and retention though the use of task specificity, repetition, and feedback; while presenting an engaging and motivating challenge for participants. Current literature has not determined the response of an individual to virtual obstacle crossing in comparison to real environment over-ground obstacle crossing, nor whether aging influences this behavior. In a first step to determine the clinical viability of a virtual reality obstacle crossing environment, this task was tested using healthy able-bodied individuals (20 younger adults and 20 older adults) to determine an individual’s expected crossing behavior during a single session of training. The purpose of this study was to (1) determine the biomechanical obstacle-crossing behavior of an able-bodied individual within a virtual environment, (2) determine if a learning effect exists with virtual obstacle crossing, and (3) determine if the learning effect will transfer to over-ground obstacle crossing and create performance changes. Dependent variables measured were foot placement before and after the obstacles for the both the lead and trail limbs, toe/heel clearance for both limbs in the vertical and radial directions, and the peak toe and heel elevation. The hypotheses were: (1) a training effect would be observed at the end of the virtual obstacle crossing training in the form of the adoption of a safer obstacle crossing strategy in the virtual environment, (2) a safer obstacle crossing strategy in the real environment would be adopted in the post-test relative to the pre-test, and (3) the performance changes in the virtual environment would be correlated with the performance changes in the real environment, suggesting an association between motor learning in a virtual environment and transfer to a real environment task. It was also postulated that each hypothesized finding would be affected by age, with older adults showing less learning and transfer (albeit still significant) compared to the younger adults. Results indicate that participants learned to cross the virtual obstacle more safely and that change in behavior was transfer to the real environment. Further, while both age groups showed transfer to the real environment task, they differed on which limb their transfer effects applied to. The data suggest it is plausible to use virtual reality training as a way to enhance gait characteristics in the context of obstacle avoidance, potentially a leading to a novel way to reduce fall risk

Neuromotor Changes in Participants with a Concussion History can be Detected with a Custom Smartphone App

Neuromotor dysfunction after a concussion is common, but balance tests used to assess neuromotor dysfunction are typically subjective. Current objective balance tests are either cost- or space-prohibitive, or utilize a static balance protocol, which may mask neuromotor dysfunction due to the simplicity of the task. To address this gap, our team developed an Android-based smartphone app (portable and cost-effective) that uses the sensors in the device (objective) to record movement profiles during a stepping-in-place task (dynamic movement). The purpose of this study was to examine the extent to which our custom smartphone app and protocol could discriminate neuromotor behavior between concussed and non-concussed participants. Data were collected at two university laboratories and two military sites. Participants included civilians and Service Members (N = 216) with and without a clinically diagnosed concussion. Kinematic and variability metrics were derived from a thigh angle time series while the participants completed a series of stepping-in-place tasks in three conditions: eyes open, eyes closed, and head shake. We observed that the standard deviation of the mean maximum angular velocity of the thigh was higher in the participants with a concussion history in the eyes closed and head shake conditions of the stepping-in-place task. Consistent with the optimal movement variability hypothesis, we showed that increased movement variability occurs in participants with a concussion history, for which our smartphone app and protocol were sensitive enough to capture

Neuromotor Changes in Participants With a Concussion History Can Be Detected With a Custom Smartphone App

Neuromotor dysfunction after a concussion is common, but balance tests used to assess neuromotor dysfunction are typically subjective. Current objective balance tests are either cost- or space-prohibitive, or utilize a static balance protocol, which may mask neuromotor dysfunction due to the simplicity of the task. To address this gap, our team developed an Android-based smartphone app (portable and cost-effective) that uses the sensors in the device (objective) to record movement profiles during a stepping-in-place task (dynamic movement). The purpose of this study was to examine the extent to which our custom smartphone app and protocol could discriminate neuromotor behavior between concussed and non-concussed participants. Data were collected at two university laboratories and two military sites. Participants included civilians and Service Members (N = 216) with and without a clinically diagnosed concussion. Kinematic and variability metrics were derived from a thigh angle time series while the participants completed a series of stepping-in-place tasks in three conditions: eyes open, eyes closed, and head shake. We observed that the standard deviation of the mean maximum angular velocity of the thigh was higher in the participants with a concussion history in the eyes closed and head shake conditions of the stepping-in-place task. Consistent with the optimal movement variability hypothesis, we showed that increased movement variability occurs in participants with a concussion history, for which our smartphone app and protocol were sensitive enough to capture

A Systematic Review of Non-Pharmacological Interventions to Improve Gait Asymmetries in Neurological Populations

Gait asymmetries are commonly observed in neurological populations and linked to decreased gait velocity, balance decrements, increased fall risk, and heightened metabolic cost. Interventions designed to improve gait asymmetries have varying methods and results. The purpose of this systematic review was to investigate non-pharmacological interventions to improve gait asymmetries in neurological populations. Keyword searches were conducted using PubMed, CINAHL, and Academic Search Complete. The search yielded 14 studies for inclusion. Gait was assessed using 3D motion capture systems (n = 7), pressure-sensitive mats (e.g., GAITRite; n = 5), and positional sensors (n = 2). The gait variables most commonly analyzed for asymmetry were step length (n = 11), stance time (n = 9), and swing time (n = 5). Interventions to improve gait asymmetries predominantly used gait training techniques via a split-belt treadmill (n = 6), followed by insoles/orthoses (n = 3). The literature suggests that a wide range of methods can be used to improve spatiotemporal asymmetries. However, future research should further examine kinematic and kinetic gait asymmetries. Additionally, researchers should explore the necessary frequency and duration of various intervention strategies to achieve the greatest improvement in gait asymmetries, and to determine the best symmetry equation for quantifying gait asymmetries

A Systematic Review of Non-Pharmacological Interventions to Improve Gait Asymmetries in Neurological Populations

Gait asymmetries are commonly observed in neurological populations and linked to decreased gait velocity, balance decrements, increased fall risk, and heightened metabolic cost. Interventions designed to improve gait asymmetries have varying methods and results. The purpose of this systematic review was to investigate non-pharmacological interventions to improve gait asymmetries in neurological populations. Keyword searches were conducted using PubMed, CINAHL, and Academic Search Complete. The search yielded 14 studies for inclusion. Gait was assessed using 3D motion capture systems (n = 7), pressure-sensitive mats (e.g., GAITRite; n = 5), and positional sensors (n = 2). The gait variables most commonly analyzed for asymmetry were step length (n = 11), stance time (n = 9), and swing time (n = 5). Interventions to improve gait asymmetries predominantly used gait training techniques via a split-belt treadmill (n = 6), followed by insoles/orthoses (n = 3). The literature suggests that a wide range of methods can be used to improve spatiotemporal asymmetries. However, future research should further examine kinematic and kinetic gait asymmetries. Additionally, researchers should explore the necessary frequency and duration of various intervention strategies to achieve the greatest improvement in gait asymmetries, and to determine the best symmetry equation for quantifying gait asymmetries

Final model and statistical results of each movement variability dependent variable.

Final model and statistical results of each movement variability dependent variable.</p

Data processing and model specification flow chart.

Abbreviations: HS = head shake, EC = Eyes-closed conditions. (A) Flow chart of the data processing. The two boxes in the bottom are the sample size submitted for the statistical analyses for all variables except CV Stride time. *1 n = the number of subjects, nt = the number of trials. *2 for CV stride time, n = 138 healthy and n = 61 concussed participants for the EC condition and n = 141 healthy and n = 60 concussed participants for the HS condition were submitted for analyses. (B) the model specification process: Fixed effects coefficients are B0, B1, B2, and B3, j = j-th group of i-th individual. u0i represents the random effect of the individual intercept, and e0i represents the residuals, where both are assumed to be normally distributed.</p

Smartphone app.

(A) Placement of the phone on the thigh and the illustration of stepping movement. (B) Representative time series of the thigh flexion angle in the sagittal plane during the stepping in place task. (C) Study design and dependent variables extracted from the smartphone app.</p

Raw data.

Dependent variable and demographic data for each participant. (XLSX)</p