Artificial Intelligence in Exercise Monitoring and Management

This narrative review article examines the integration of artificial intelligence (AI) in exercise monitoring and management, highlighting its role in health surveillance and disease management. It discusses how exercise and physiological indicators, such as gait and cardiorespiratory fitness, are utilized to assess health outcomes. The review outlines the advantages of AI in improving the precision of monitoring, diagnosis, and personalized exercise prescriptions compared to traditional methods. However, it also addresses challenges such as limited data quality, issues with multimodal integration, and ethical concerns regarding privacy. The authors synthesize current findings, identify research gaps, and propose future directions to enhance the effectiveness of AI-driven approaches in exercise and health research. The review emphasizes the importance of exercise indicators as objective measures of health and their potential to inform individualized exercise interventions, ultimately aiming to improve health outcomes and disease management.