Hybrid Brain-Computer Interaction for Functional Motor Recovery after Stroke

Abstract

BCI technology can encourage motor training and practice by offering an on-line feedback about brain signals associated with mental practice, motor intention/attempt and other neural recruitment strategies, and thus helping to guide neuroplasticity to improve recovery. To deploy an EEG-based BCI system as an effective post-stroke rehabilitation training tool, it is crucial that the BCI design incorporates some principles of current rehabilitative settings suitable to stimulate patients’ engagement during exercise. Here we report on a comprehensive BCI-driven rehabilitative system which can monitor not only the practice of a mental motor tasks but also the residual muscular patterns of the affected limb, and it eventually drives a Functional Electrical Stimulation device to close the loop between motor intention and sensory perception. The ultimate goal is to let the patients re-learn their motor scheme by having voluntary (covert and/or overt) access to the affected limb.

This work is supported by the European ICT Programme Project FP7-224631 This paper only reflects the authors’ views and funding agencies are not liable for any use that may be made of the information contained herein.