Introduction Homework-based rehabilitation programs can help stroke survivors restore upper extremity function. However, compensatory motions can develop without therapist supervision, leading to sub-optimal recovery. We developed a visual feedback system using a live video feed or an avatar reflecting users' movements so users are aware of compensations. This pilot study aimed to evaluate validity (how well the avatar characterizes different types of compensations) and acceptability of the system. Methods Ten participants with chronic stroke performed upper-extremity exercises under three feedback conditions: none, video, and avatar. Validity was evaluated by comparing agreement on compensations annotated using video and avatar images. A usability survey was administered to participants after the experiment to obtain information on acceptability. Results There was substantial agreement between video and avatar images for shoulder elevation and hip extension (Cohen's κ: 0.6–0.8) and almost perfect agreement for trunk rotation and flexion (κ: 0.80–1). Acceptability was low due to lack of corrective prompts and occasional noise with the avatar display. Most participants suggested that an automatic compensation detection feature with visual and auditory cuing would improve the system. Conclusion The avatar characterized four types of compensations well. Future work will involve increasing sensitivity for shoulder elevation and implementing a method to detect compensations.
Is it possible to assess the effects of dynamic arm supports on upper extremity range of motion during activities of daily living in the domestic setting using a portable motion capturing device? – A pilot study
