Advanced Machine Learning Approaches in Human-Machine Interaction for Rehabilitation Exoskeleton
Copyright © 2026, IEEE
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Abstract
Excerpt: The rapid advancements in autonomy and Human-Machine Interaction have significantly influenced the development of exoskeletons for assistive and rehabilitative applications. Deep learning approaches have emerged as a transformative tool, offering enhanced control strategies and promising improved outcomes in exoskeleton-based interventions. This review paper provides a comprehensive exploration of recent advancements in deep learning methods applied to exoskeleton control, focusing on state-of-the-art developments in autonomy.
This paper has been withdrawn.