Data-Driven Rehabilitation Using Machine Learning Approaches for Adaptive Recovery and Treatment

Abstract

Rehabilitation is undergoing a revolution with machine learning (ML) enabling personalized solutions based on patient-specific data. Unlike current rehabilitation practices that lack adaptability, ML optimizes physical, cognitive, and psychological aspects through real-time monitoring, modeling, and intervention. Computer vision enhances movement analysis, NLP supports psychological assessments, and predictive models optimize treatment plans. Applications such as wearable technology, telerehabilitation, and ML-driven robotics improve patient interaction and supervision, offering flexible and remote care. Integrating ML with technologies like VR and IoT creates patient-centric, accessible solutions with superior prognostic value. These advancements usher in a new era of algorithms designed for better patient care, safety, and personalized therapeutic processes.