Work

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

Year: 2025

Type: conference-paper

Abstract: 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.

Source: ACM Conference on User Modeling, Adaptation and Personalization (UMAP)

DOI: 10.1145/3699682.3727565

Author: Victor Garcia

Institution: Universidad Nacional de Educación a Distancia

Language: English

Topic: Human Pose and Action Recognition

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

OpenAlex ID: W4411280585

FWCI:

Cites: 13

Cited by:

Related to: 10