Tracking Post-stroke Walking Improvements From the Clinic Into the Home

The purpose of this proposal is to use novel video-based movement tracking technology to measure gait quality after stroke - in the home. Current rehabilitation practice assesses walking in the highly controlled 'ideal' clinical environment. The implicit assumption by clinicians and researchers is that the way people walk in the clinic (their best capacity) reflects the way they walk in the real-world (true performance). With advances in computer vision and development of pose estimation algorithms, it is now possible to directly measure how people are walking in their homes. It is critical that researchers apply this technology to examine the basic assumptions that underlie current rehabilitation practice. Here, a video-based pose estimation workflow will be used to 1) contrast the gait patterns of persons post-stroke as observed in-clinical vs. in-home settings, and 2) map the rate of deterioration of clinically-derived walking improvements, in the home. This methodology has been used to accurately measure gait kinematics in people with stroke as they walk in laboratory, however this study now seeks to use these methods to record people with stroke as they walk in their natural home environments. The ultimate outcome of this project will not only be freely-available video-based workflow modified for home-based gait assessments, but also preliminary data revealing how people with stroke walk in the real world.