A novel approach to promote upper-limb motor recovery in stroke survivors using assistive myoelectric control and adaptive visual feedback in virtual reality.

Myoelectric control may offer an engaging and effective modality for post-stroke rehabilitation. By translating residual muscle activity into control signals for virtual or robotic interfaces, it enables patients to actively participate in therapeutic tasks, even when voluntary movement is limited. However, stroke patients often exhibit abnormal muscle activation patterns, which can limit the effectiveness of such approaches. To address this, we developed a novel assistive-adaptive algorithm designed to enhance myoelectric control by promoting the learning of more functional and physiologically plausible muscle activation patterns. The algorithm operates by projecting the patient's instantaneous muscle activity onto reference patterns, each associated with a specific movement direction. These reference patterns are selected to minimize co-contraction while maintaining high similarity to physiological muscle patterns. The output of the projection determines the direction of the assistive force provided within a virtual isometric reaching task, while the level of assistance is modulated in real-time to progressively stimulate active participation, a key factor for promoting neuroplasticity. We evaluated the system through pilot experiments with three chronic stroke patients, focusing on changes in movement planning and accuracy and on the alignment toward physiological activation patterns. Our results revealed heterogeneous but promising trends, with three participants demonstrating improvements across multiple metrics after short exposure to the assistive algorithm. Specifically, higher similarity of muscle patterns to healthy participants was often aligned with better motor performance. These findings support the feasibility of using projection-based EMG assistance to guide patients toward more effective muscle recruitment strategies. The proposed framework establishes a foundation for future longitudinal studies aimed at testing whether such short-term adaptations can consolidate into lasting neuromuscular changes, potentially enhancing functional recovery through repeated and targeted exposure to myoelectric assistance.