Artificial Intelligence-Driven Physiotherapy for Personalized Pain Assessment and Rehabilitation: Integrating Wearable Sensors, Digital Biomarkers, and Predictive Analytics

Chronic musculoskeletal pain is a major contributor to disability, functional impairment, and reduced quality of life worldwide, creating substantial challenges for healthcare systems and rehabilitation services. Conventional pain assessment and physiotherapy approaches often rely on subjective patient reporting and periodic clinical evaluations, limiting their ability to capture the dynamic and multidimensional nature of pain and recovery. Recent advances in artificial intelligence (AI), wearable sensor technologies, digital biomarkers, and predictive analytics have created new opportunities for developing more objective, personalized, and data-driven rehabilitation strategies. This narrative review examines the emerging role of AI-driven physiotherapy in personalized pain assessment and rehabilitation, with particular emphasis on the integration of wearable sensors, digital biomarkers, and machine learning-based predictive models. The review discusses current challenges in pain assessment and rehabilitation, the technological foundations of AI-assisted physiotherapy, and the growing application of wearable devices for monitoring physiological, behavioral, and functional parameters. Furthermore, the potential of predictive analytics to support pain prediction, rehabilitation outcome forecasting, risk stratification, and clinical decision-making is explored. Evidence from clinical applications in osteoarthritis, chronic low back pain, postoperative orthopedic rehabilitation, and age-related functional decline demonstrates the capacity of AI-assisted systems to enhance treatment personalization and improve rehabilitation outcomes. Despite promising developments, challenges related to data quality, model interpretability, privacy, regulatory compliance, and clinical integration remain important barriers to widespread adoption. Future advancements are expected to focus on multimodal data integration, explainable artificial intelligence, remote monitoring, and precision rehabilitation frameworks. Overall, the convergence of AI technologies, wearable sensors, digital biomarkers, and predictive analytics has the potential to transform physiotherapy practice by enabling more accurate pain assessment, individualized rehabilitation planning, improved functional recovery, and enhanced patient-centered care.