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Shaping Voluntary Rehabilitation Behaviour through sEMG-based Human-Machine Collaboration: A Systematic Review
DescriptionThis systematic review examined how surface electromyography (sEMG)-based human-machine collaborative control supports voluntary participation in rehabilitation for individuals with motor impairment. Following PRISMA guidelines, five databases were searched, and 91 studies were included in the main review, with 7 supplementary studies retained to support interpretation of neuroplasticity and psychological-behavioural mechanisms. Across the reviewed studies, sEMG mainly entered the rehabilitation control loop through intention-driven control, contribution regulation, and parameter regulation. These roles supported variable impedance control, admittance or compliant control, assist-as-needed control, shared control, and sliding mode control, and were further reflected in function-oriented active training, ability-adaptive training modes, and state and feedback regulation. Overall, the findings suggest that sEMG is increasingly used not only to detect movement intention but also to organize assistance, training progression, and feedback updating. We therefore propose a human-centred Effort-to-Engagement framework. Future work should evaluate sEMG-based collaborative control in more ecologically valid and clinically grounded settings.