Ambulating in community environments requires the skills to cope with multiple, simultaneous dimensions such as walking speed and distance, etc. Such skills remain compromised in the majority of stroke survivors due to insufficient or lack of targeted practice. The investigators propose to test a new, individually-tailored intervention, developed by the research team, grounded in best evidence in community ambulation, principles of motor learning and participatory action research. This unique intervention will combine virtual reality (VR) and field training practice to optimize learning that can be generalized to daily walking activities.
Participants will engage in the 4-week, individually-tailored intervention that comprises of supervised VR training sessions (3 times/week) performed in the clinical setting. VR sessions will be completed by field training assignments. Subjects will be assessed twice prior to the intervention, immediately after the intervention and at follow up.
Generalized estimating equations will be used to compare changes in main and secondary outcomes across time points, with each personal factor of interest (e.g. walking capacity, visual-perceptual function, and cognitive function) analyzed individually while adjusting for age. Outcomes on adherence, safety and acceptability will be analyzed with descriptive statistics.
Required sample size was estimated based on Green's rule (effect size=0.5, power=80%, α=0.05) with a variance inflation factor assuming moderate within-subject correlations for 3 post-baseline measurement time points. This yields a sample size of 30. Assuming a worst-case scenario of 30% attrition rate, a total of 40 stroke subjects (20/site) will be recruited.