SleeveAR: Augmented Reality for Rehabilitation using Realtime Feedback

We present an intelligent user interface that allows people to perform rehabilitation exercises by themselves under the offline supervision of a therapist. Every year, many people suffer injuries that require rehabilitation. This entails considerable time overheads since it requires people to perform specified exercises under the direct supervision of a therapist. Therefore it is desirable that patients continue performing exercises outside the clinic (for instance at home, thus without direct supervision), to complement in-clinic physical therapy. However, to perform rehabilitation tasks accurately, patients need appropriate feedback, as otherwise provided by a physical therapist, to ensure that these unsupervised exercises are correctly executed. Different approaches address this problem, providing feedback mechanisms to aid rehabilitation. Unfortunately, test subjects frequently report having trouble to completely understand the feedback thus provided, which makes it hard to correctly execute the prescribed movements. Worse, injuries may occur due to incorrect performance of the prescribed exercises, which severely hinders recovery. SleeveAR is a novel approach to provide real-time, active feedback, using multiple projection surfaces to provide effective visualizations. Empirical evaluation shows the effectiveness of our approach as compared to traditional video-based feedback. Our experimental results show that our intelligent UI can successfully guide subjects through an exercise prescribed (and demonstrated) by a physical therapist, with performance improvements between consecutive executions, a desirable goal to successful rehabilitation.