JMIR Publications

ABSTRACT

Physical therapy is essential for the successful rehabilitation of common shoulder injuries and following shoulder surgery. Patients may receive some training and supervision for shoulder physiotherapy through private pay or private insurance, but they are typically responsible for performing most of their physiotherapy independently at home. It is unknown how often patients perform their home exercises and if these exercises are done correctly without supervision. There are no established tools for measuring this. It is therefore unclear if the full benefit of shoulder physiotherapy treatments are being realized. Our team has recently developed a Smart Physiotherapy Activity Recognition System (SPARS) for tracking home shoulder physiotherapy exercises using sensors in a commercial smart watch and artificial intelligence (AI). SPARS was successful in identifying shoulder exercises in healthy adults in the laboratory setting. Further inquiry is required to establish the clinical effectiveness of this technology and investigate the potential individual and societal impacts of its use. The proposed research will 1) Further develop and validate the SPARS technology for evaluating adherence to shoulder exercise participation and technique in a clinical patient population with rotator cuff pathology, advancing the state-of-the-art in rehabilitation engineering AI. 2) Use SPARS to quantify the rate of home physiotherapy adherence, determine the effects of adherence on recovery, and identify barriers to successful adherence; leading to novel actionable insights on current treatment protocols. 3) Develop and pilot test an ethically conscious SPARS-powered rehabilitation program that individualizes patient-care based on their adherence. A careful examination of the ethical and policy challenges related to surveillance for self-managed medical treatments will help ensure SPARS and related technologies be deployed conscientiously and to a benefit of patients and society.