Promoting continuous rehabilitation with AI-based motion capture and biomechanical analysis: objective feedback as a catalyst.

Introduction: Exercise therapy is effective for various diseases, but one of the problems in rehabilitation is "continuity" and preventing quitting. This study assumes that objectively tracking changes in motor skills and providing feedback may contribute to the continuity of rehabilitation. Upper limb joint moments were estimated by our program using coordinates obtained through AI-based markerless motion capture. This study aimed to visualize and provide feedback on participants' assessments of their motor function to promote an understanding of changes in their motor function and to improve their motivation to participate in the exercise. Then, the promoting effect of the feedback is examined with a questionnaire. Methods: Participants were late-stage elderly ( Results: The t-test was performed on each partial regression coefficient, and Parkinsonism participants had significantly negative values compared to those in other disease groups ( Discussion: As indicated by the changes in the scores of the questionnaire survey in this study, the participants' motivation to participate improved after the feedback was given; however, these positive effects had disappeared in the measurement one month later. Thus, continuous feedback more than once per month seems to be required to keep motivation to exercise.