The burden of stroke on the health care system at large and individual patients is profound, and current techniques for rehabilitation rely on the training and dedication of the rehabilitation specialist. Here we present an immersive, virtual reality environment for presenting feedback to subjects in the form of a set of virtual hands. By just imagining the use of the left or right hands, subjects could see movement in the virtual hands and learn to modulate their thoughts to control them. Allowing subjects task relevant motor feedback early could prove an effective means of early rehabilitation. The implications of this training are presented in 6 patients who had suffered cortical or basal ganglia stroke. Using the system described below, the subject's were able to achieve control accuracies of as high as 81% in a binary classification task and showed progression of skill in as little as three, two-hour experimental sessions.
University of Minnesota M.S. thesis. June 2013. Major: Biomedical Engineering. Advisor:
Bin He. 1 computer file (PDF); v, 34 pages.
Doud, Alexander James.
Motor imagery retraining after stroke with virtual hands: an immersive sensorimotor rhythm-based brain-computer interface.
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