Friday, January 27, 2012

A Pilot Study of Brain-Computer Interface (BCI)-Driven Orthosis for Rehabilitation

The Joint UNC-NCSU Rehabilitation Engineering Center Pilot Grant Program Makes First Two Awards

The Rehabilitation Engineering Center announces the awards of two pilot grants totaling $50K to facilitate collaboration between UNC and NCSU faculty for attaining larger grants, and to foster collaboration between undergraduate engineers at NCSU/UNC and Health Sciences students at UNC. These two grants will foster advancement of clinically relevant rehabilitation engineering research.

Co-Principal Investigators

Chang S., Nam Ph.D., Industrial and Systems Engineering, NCSU

Richard Goldberg Ph.D., Biomedical Engineering NCSU/UNC-Chapel Hill

Title: A Pilot Study of Brain-Computer Interface (BCI)-Driven Orthosis for Rehabilitation

This project aims at determining the ability of stroke patients to volitionally modulate their sensorimotor rhythms and operate a brain-actuated hand orthosis with additional somatosensory feedback through a newly established interdisciplinary collaboration between UNC-CH (Biomedical Engineering) and NCSU (Industrial and Systems Engineering) research teams. Subjects equipped with a BCI-orthosis system perform hand grasping, hand opening, wrist extension, and wrist bending by imagining movements of left hand, right hand, both hands, and both feet, respectively, while receiving visual and haptic feedback. We expect that haptic feedback in addition to visual feedback about the current state of brain activity improves performance of the BCI driven orthosis and that this motor imagery-based BCI training with sensory feedback can be utilized to support the process of cortical reorganization required for clinical improvement in impaired motor function. Results of the present study will help us better understand neural mechanisms of a BCI-orthosis operation. Findings from this study will also allow us to conduct long-term rehabilitation studies with stroke patients who have severe motor impairment using a BCI-driven prosthetic connected to a motor imagery-based Wolfpack BCI system we developed.

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