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Intelligent Rehabilitation: Advances in Artificial Intelligence for Musculoskeletal Rehabilitation: A Narrative
Jiayue Hao1, Shibo Sun2, Tianxu Dou3
1Department of Orthopaedics, The First Hospital of China Medical University, Shenyang, Liaoning, People's Republic of China.
None:
Musculoskeletal diseases, such as osteoarthritis and joint trauma, significantly impact patient mobility, independence, and quality of life. With the rising demand for effective and accessible rehabilitation strategies, artificial intelligence (AI) has emerged as a powerful tool to support diagnosis, surgical planning, and personalized rehabilitation. This narrative review summarizes recent advances in the application of AI in musculoskeletal disease management, with a particular emphasis on postoperative and conservative rehabilitation. We outline the foundational concepts of AI, including machine learning, deep learning, computer vision, and natural language processing, and discuss their roles in clinical decision-making and recovery monitoring. Furthermore, we examine emerging AI-assisted rehabilitation tools, including mobile applications, robotic exoskeletons, gamified platforms, and markerless motion tracking systems, which collectively enhance treatment precision, patient adherence, and remote care capabilities. Despite promising outcomes, current limitations include insufficient personalization, limited multimodal data integration, and inadequate clinical validation. Future developments should focus on improving model interpretability, integrating real-time biosensing, and optimizing user interface design to support clinically feasible and patient-centered musculoskeletal rehabilitation.
