Artificial Intelligence in Physiotherapy Rehabilitation: Current Applications and Future Directions

Abstract

AI has the potential to revolutionize physiotherapy rehabilitation through better movement assessment accuracy, personalized treatment, patient monitoring, and decision-making. The purpose of this review is to provide an overview of the current use of AI in physiotherapy rehabilitation. Specifically, the review considers the following domains in physiotherapy rehabilitation: movement analysis, exercise prescription based on machine learning, robotic rehabilitation, use of wearables, telerehabilitation, and predictive analytics. In addition, the review critically assesses the methodology underlying the research on developing and validating AI technology. According to the findings, AI has great potential to enhance objective movement assessment, improve rehabilitation programs, allow remote patient management, and enable data-driven decision-making in clinical practice. However, even though technological progress is promising, the evidence base is characterized predominantly by feasibility and technical studies and small-scale clinical trials, while there are only few studies proving the clinical effectiveness of these innovations through large randomized controlled trials. Some of the challenges in the field of AI in physiotherapy rehabilitation are lack of diverse datasets, algorithmic transparency, data protection issues, inequality in access to AI innovations, regulatory uncertainty, and insufficient trust and training of clinicians.