Awareness of Artificial Intelligence-Based Rehabilitation Among Physiotherapy Students: A Cross-Sectional Survey

Background: Artificial Intelligence is increasingly integrated into rehabilitation through robotics, tele-rehabilitation platforms, clinical decision support systems, and wearable technologies. As future rehabilitation professionals, physiotherapy students must be adequately prepared to understand and utilize these innovations. However, limited evidence exists regarding their level of awareness and readiness to adopt artificial intelligence-based rehabilitation practices. Objective: To assess the level of awareness, understanding, and perceived value of AI-based rehabilitation among physiotherapy students. Methodology: A cross-sectional survey was conducted among physiotherapy students using a structured, self-administered questionnaire. The instrument captured demographic information, general awareness of artificial intelligence, and domain-specific knowledge related to artificial intelligence applications in rehabilitation. Key domains included prior exposure, conceptual understanding, practical application, and perceived benefits of artificial intelligence-driven rehabilitation technologies. Results: The findings revealed an overall low level of awareness among participants, particularly in terms of experiential and practical knowledge of artificial intelligence applications in rehabilitation. While a proportion of students demonstrated basic theoretical familiarity with artificial intelligence concepts, there was a notable gap in their ability to translate this knowledge into clinical practice. Despite this, most participants recognized the potential of artificial intelligence to enhance efficiency, learning, and patient outcomes. This disparity highlights a disconnect between conceptual awareness and functional competency. Conclusion: The study underscores the urgent need to integrate comprehensive artificial intelligence-related training into physiotherapy education. Curriculum reforms should focus on both foundational artificial intelligence concepts and their practical application in rehabilitation settings to better prepare students for technology-driven clinical practice.