Towards Personalized Physiotherapy via Common Semantic Fusion: Multi-Modal Learning, Computer Vision and Empathetic NLP

This research develops an AI-driven framework for personalized physiotherapy by integrating multi-modal learning, computer vision, and empathetic NLP.It focuses on user modeling and personalization to enhance physiotherapy assessments via an optimized YOLO Pose algorithm, fusing visual, auditory, and textual data for comprehensive mobility evaluation.Preliminary results show improved pose estimation, supporting the potential for clinical validation and integration of additional modalities such as inertial sensors.