Tracking Knee Rehabilitation at Home Using a Smart IoT Wearable Triaxial Accelerometer

Abstract

With the rapid progression of population aging, degenerative osteoarthritis has become one of the most prevalent conditions among older adults, leading to increasing demands for knee rehabilitation, particularly after joint degeneration and surgery. Conventional rehabilitation models are constrained by medical resources and clinical settings, making it difficult to provide long-term and real-time monitoring of exercise performance and safety. This study proposes a home-based knee rehabilitation monitoring and alert system that utilizes a wearable triaxial accelerometer to continuously acquire knee motion data, including joint range of motion, repetition counts, and holding time of each exercise. The collected signals are transmitted wirelessly to a cloud platform for data storage and analysis. Based on prescribed rehabilitation protocols and individualized safety thresholds, the system automatically identifies potential risk conditions during exercise, such as excessive joint angle, prolonged holding time, abnormal movement patterns, and unexpected interruption of training, and delivers timely alert notifications to caregivers or healthcare professionals via mobile devices. Preliminary findings indicate that, when combined with professional therapists’ review and feedback, the proposed home-based rehabilitation mechanism can improve adherence to rehabilitation exercises, reduce the risk of improper movements, and support remote monitoring by clinicians. These results suggest that the system may serve as a valuable foundation for developing intelligent rehabilitation support systems and remote care services.