Brain-Computer Interface in Chronic Stroke: an Application of Sensorimotor Closed-loop and Contingent Force Feedback

Motor rehabilitation after stroke injury is highly important since the number of people suffering this disease is constantly increasing. Brain-Computer Interfaces (BCIs) have been recently used in the recovery of motor functions: in particular, the closed loop involving sensorimotor brain rhythms, assistive-robot training and proprioceptive feedback in an operant learning fashion might be potentially one of the most effective ways to promote the neural plasticity of the ipsilesional brain hemisphere and to restore motor abilities. This study aimed at implementing such a scheme: one chronic stroke patient was recruited and underwent the experiment using both the damaged and the healthy arm, considered as control during the following analysis. Kinematic and neurophysiological outcomes confirmed the efficacy of this treatment and supported the hypothesis that a contingent force feedback can improve motor functions of the upper limb.