Effectiveness of AI-Supervised Mobile Exercise Application in Patients With Knee Osteoarthritis

This study aims to evaluate the effectiveness of an artificial intelligence (AI)-supported mobile application that supervises home-based exercise programs in patients with knee osteoarthritis. A total of 80 participants aged 40 to 80 will be randomly assigned to one of two groups: a mobile application exercise group or a home exercise booklet group. Both groups will receive the same standardized stretching, strengthening, and range of motion exercises designed for knee osteoarthritis. The mobile app provides real-time feedback and supervision using the device\'s camera and artificial intelligence algorithms to track and guide exercise performance. Participants in the app group will perform exercises with supervision via the app interface, while the control group will follow the same exercises using printed instructions. Both groups will exercise 3 to 4 times per week for 4 weeks. The study will compare pain levels, physical function, and balance before and after the intervention using validated outcome measures such as the WOMAC Index and the Visual Analog Scale. This study may help determine whether AI-supported digital tools can improve exercise adherence and outcomes in patients with knee osteoarthritis.