Utilizing Artificial Intelligence to Augment Physiotherapy Education: A Video-Based Analysis and Grading System for Evaluating Student Therapists' Performance

The rapid evolution of artificial intelligence (AI) has ushered in new opportunities for enhancing physiotherapy education. This study introduces an innovative AI-based tool that integrates computer vision and speech recognition to provide a comprehensive and objective assessment of physiotherapy students' practical skills. Designed to surpass the limitations of traditional, subjective methods, this system analyses both physical movements and verbal interactions during exams, categorizing student performance into 'Good', 'Average', or 'Brief' to offer a multifaceted evaluation of their clinical abilities. The research aimed to develop and validate a system that accurately captures and analyses nuanced physical and verbal behaviours in physiotherapy practical exams. The system was trained and tested on a curated dataset of recorded sessions, where it demonstrated high precision, achieving an overall accuracy of 89% in identifying specific actions performed by students. These results underscore the system's capability to enhance the objectivity and depth of practical assessments significantly. This study marks a significant contribution to healthcare education by showing the effectiveness of AI technologies in assessing practical and communication skills. The AI-assisted tool not only improves the educational process but also better prepares students for clinical practice. The findings suggest a model for future AI integration in professional healthcare training and assessment, highlighting the transformative potential of AI in advancing physiotherapy education.