Human-Robot Interaction in Lower Limb Rehabilitation: A Scoping Review

The rising prevalence of chronic diseases and an aging population have led to a significant increase in disability rates worldwide. Stroke, a major cause of disability, necessitates effective rehabilitation strategies to restore lost motor functions in the lower limbs. Human-robot interaction (HRI) in lower limb rehabilitation offers promising solutions, providing personalized feedback and intensive, repetitive training to enhance motor recovery. While personalized feedback and adaptive assistance have shown promise in enhancing rehabilitation outcomes, there remains limited exploration of how these elements can be optimized through machine learning and other advanced technologies. This review aims to bridge these gaps by systematically examining the design criteria for effective human-robot interaction (HRI) systems, evaluating various modalities employed in robotic rehabilitation, and analyzing control strategies that enhance user outcomes. By delving into these areas, our review seeks to provide a comprehensive understanding of HRI in lower limb rehabilitation, offering a foundation for future research and development in this critical field. By integrating advanced technologies with personalized rehabilitation approaches, HRI systems can adapt more effectively to individual patient needs, maximizing their potential to improve rehabilitation outcomes. Finally, our review emphasizes the importance of interdisciplinary collaboration in advancing HRI systems for lower limb rehabilitation.