Technology in Physiotherapy: A Bibliometric Analysis of Artificial Intelligence in Physiotherapy and Rehabilitation

Abstract

Objective: This study aimed to perform quantitative and qualitative evaluations of the state of artificial intelligence (AI) for physiotherapy and rehabilitation. Materials and Methods: The bibliometric data have been collected using title and abstract keyword searches from the Web of Science database for AI applications in the physiotherapy field. A total of 187 articles were identified using keywords such as machine learning, deep learning, artificial neural network, artificial intelligence, natural language processing, and physiotherapy. Results: A total of 187 articles published between 2001 and 2024 were analyzed. The year 2023 had the highest publication volume (47 articles). “Engineering Electrical Electronic” was the most productive research field. Frequently occurring terms included “Machine Learning,” “Rehabilitation,” and “Artificial Intelligence.” Conclusions: Publications on artificial intelligence and physiotherapy have significantly increased in recent years. These findings underscore the increasing relevance of AI-driven technologies for clinical practice, therapeutic decision-making, and rehabilitation research. For physiotherapists, healthcare professionals, and interdisciplinary researchers, this study provides valuable insight into emerging trends and areas of concentration. Future work can benefit from bibliometric analyses across different databases to support multidisciplinary research.