Digital Course and Precision Rehabilitation for Knee Osteoarthritis and Older Adults: Integration of Multisensory Stimulation and Digital Twin Technology

Knee osteoarthritis (OA) is a common degenerative joint disease in middle-aged and older adults and is frequently associated with pain, quadriceps weakness, reduced mobility, impaired proprioception, balance deficits, and limitations in daily functional activities. Exercise therapy is recommended as a first-line conservative treatment for early to moderate knee OA; however, conventional rehabilitation programs often rely on therapist supervision and lack objective, quantitative movement monitoring, real-time feedback, and personalized adjustment for home-based training. These limitations may reduce exercise adherence and make it difficult to ensure correct movement execution outside the clinical setting. The overall aim of this study is to develop and evaluate a digital rehabilitation exercise program and user interface for individuals with arthritis, using a smart elastic knee brace integrated with wearable sensing technology, surface electromyography biofeedback, joint-angle monitoring, multisensory stimulation, and artificial intelligence-based musculoskeletal monitoring. The proposed system is designed to provide personalized digital rehabilitation courses, real-time visual and auditory feedback, and objective assessment of movement performance to support knee joint motor control, gait retraining, and individualized rehabilitation planning for patients with knee OA. The investigators hypothesize that digital rehabilitation courses combined with multisensory stimulation, including neuromuscular electrical stimulation and vibration, will improve functional performance, movement quality, muscle activation, proprioception, and knee-related symptoms in patients with knee OA compared with conventional home exercise or gait retraining alone. The expected outcome of this study is to establish the feasibility, reliability, and clinical utility of a smart knee brace-based digital rehabilitation system for personalized knee OA management. This study will achieve the fol