Supporting Functional Tasks in Bi-Manual Robotic Mirror Therapy by Coupling Upper Limb Movements Based on Virtual Reality

Mirror therapy has been proven to be an effective rehabilitation method in hemiparetic stroke patients. Propri-oceptive feedback, which is considered important for effective rehabilitation and increased neuroplasticity, could further improve the positive rehabilitation effects of mirror therapy. Here, we propose and test a control algorithm for a bi-manual rehabilitation exoskeleton (ALEx-RS, Wearable robotics) that moves the hemiparetic arm of the patient. Specifically, the movement of the affected arm is coupled to the healthy arm via robotic assistance in the context of functional tasks in virtual reality, thereby providing task-relevant proprioceptive feedback. We tested the algorithm on ten healthy subjects in two virtual scenarios. An analysis of the exoskeleton forces and kinematics shows that MirA can provide haptic feedback to the guided arm, while simultaneously assisting the movement. The participants showed a learning effect in the functional tasks over four sessions. These results suggest, that MirA could be used for motor rehabilitation for hemiparetic stroke patients.