Brain-Computer Interface for Stroke Rehabilitation

Abstract

Recent advances in computer science enabled people with severe motor disabilities to use brain-computer interfaces (BCI) for communication, control, and even to restore their motor disabilities. This paper reviews the most recent works of BCI in stroke rehabilitation with a focus on methodology that reported on data collected from stroke patients and clinical studies that reported on the motor improvements of stroke patients. Both types of studies are important as the former advances the technology of BCI for stroke, and the latter demonstrates the clinical efficacy of BCI in stroke. Finally some challenges are discussed.

Workshops of the eighth international brain–computer interface meeting: BCIs: the next frontier

“…In the area of motor imagery and stroke rehabilitation, deep learning methods and convolutional neural networks (CNN) have been used for participant specific [255,256], participant-independent [257], and adaptive classifiers [258]. CNNs have also been used in assistive robot control with online adaptive motor classification [259].…”