Brain-Computer Interface for Motor Rehabilitation

Abstract

Stroke is the fifth leading cause of death and disability in the United States with approximately 6.8 million people living with residual deficits and approximately $34 billion spent on treatment annually [1, 2]. Simultaneously, dramatic healthcare shifts have limited extended care accessibility, with many individuals discharged from restorative therapy by three-months post-stroke. Decreased access and increased costs have led clinicians, and scientists to investigate more effective and efficient interventions to improve the function of the hemiparetic upper extremity of individuals post-stroke. One such modality is a brain-computer interface (BCI) technology that utilizes brain signals to drive rehabilitation of motor function. Emerging data suggests the use of BCI for motor rehabilitation post-stroke, facilitating an individual’s return to function and improving quality of life [3–10]. Specifically, integration of virtual reality (VR) and functional electrical stimulation (FES) components is an innovative rehabilitation strategy with a strong potential to reinstitute central motor programs specific to hand function in patients’ status post-stroke. By utilizing the Fugl-Meyer Assessment (FMA), researchers can monitor the motor function of the hemiparetic upper extremity pre/post-intervention, objectively quantifying the effectiveness of BCI for the restoration of upper extremity motor function [11]. Neurophysiological brain imaging techniques allow tracking changes in the neural substrates of motor function due to BCI intervention. Therefore, the purpose of our study is to demonstrate the utility of BCI-VR-FES intervention for motor rehabilitation of upper extremity, based upon the theory of neuroplasticity, in individuals’ post-stroke by using functional (FMA) and neurophysiological outcome measures.