Comprehensive Review on Wearable and Non-Contact Knee Health Monitoring Systems using Multimodal Sensors and Machine Learning

Knee health problems like osteoarthritis (OA), ligament injuries, and patellar displacement are a major cause of knee disability, and they will reduce quality of life worldwide. Early detection and continuous monitoring of knee health are essential for preventing disease and improving the quality of life. Existing methods such as X-ray, MRI, and arthroscopy provide detailed information but are expensive and unsuitable for long-term or home health monitoring. Nowadays, advancement methods have been made in contact-based sensors, noninvasive techniques, and artificial intelligence (AI)-based approaches to enable remote, real-time knee health assessment. Across review studies, wearable and imaging technologies show promise for detecting subtle abnormalities, such as patellar displacement and early OA changes, supporting rehabilitation and improving postsurgical recovery and imaging technologies show promise for detecting subtle abnormalities, such as patellar displacement and early OA changes, supporting rehabilitation and improving postsurgical recovery.