Applications of Artificial Intelligence in Sports Rehabilitation: Current Applications, Challenges, and Their Impact on Health and Physical Education - Shi, Zhiming; Chen, Junjie; Cheng, Guangxin (Journal of Education, Health and Sport, 2026)
Background:Exercise rehabilitation plays an essential role in improving motor function, promoting health, and enhancing quality of life among individuals with functional impairments, chronic diseases, and older adults. However, traditional rehabilitation models face limitations, particularly in long-term and home-based settings, due to subjective assessment methods, limited feedback, and low exercise adherence. Recent advances in artificial intelligence (AI) have introduced new opportunities for objective assessment, personalized intervention, and continuous monitoring in exercise rehabilitation. Objective:This review aims to summarize current applications of AI in exercise rehabilitation, evaluate its effects on motor function and health-related outcomes, identify key challenges, and discuss implications for health promotion and physical education. Methods:A narrative review approach was employed to synthesize studies on AI-assisted exercise rehabilitation, focusing on movement assessment, personalized training, feedback mechanisms, home-based rehabilitation, and applications across different populations. Results:Evidence indicates that AI-assisted exercise rehabilitation can improve movement quality, motor function, and exercise adherence. AI-based systems support objective and continuous assessment, enable individualized training programs, and enhance user engagement through real-time feedback. Nevertheless, challenges remain related to data quality, system adaptability, ethical and privacy concerns, professional training, and integration into healthcare and educational systems. Conclusion:Artificial intelligence represents a promising supportive tool in exercise rehabilitation, offering new possibilities for health promotion and physical education. Although current findings are generally positive, further high-quality research and interdisciplinary collaboration are required to support standardized, ethical, and sustainable implementation.