Meaningful Data When Exercising in XR: Involving Stroke Patients and Rehabilitation Professionals in the Design of a Platform for Home Exercise Monitoring

Background/Objectives: Stroke rehabilitation increasingly relies on intensive, task-specific upper limb training. Independent practice, for instance with extended reality (XR) technologies, introduces challenges for monitoring performance and providing meaningful feedback. Therapists need insight into whether exercises are performed as intended, while patients require accessible cues to support self-directed training. This study explored therapists’ data needs to inform the design of an XR-supported data platform. Methods: Using a human-centered design approach, we conducted focus groups, patient interviews, and data-physicalization sessions. Results: Participants emphasized the importance of session data (e.g., duration, frequency) alongside detailed exercise-specific measurement data such as range of motion and compensatory movements. Preferred data visualizations included simple, easily interpretable cues (e.g., color coding) and concise graphical overviews, enabling rapid assessment. Therapists particularly stressed insight into compensatory patterns. Conclusions: Together, the complementary methods yielded a nuanced understanding of the content and visualization requirements needed to design XR-supported independent rehabilitation.