Optimizing Hand Rehabilitation Post-Stroke Using Interactive Virtual Environments

The complexity of sensorimotor control required for hand function as well as the wide range of recovery of manipulative abilities makes rehabilitation of the hand most challenging. The investigators past work has shown that training in a virtual environment (VE) using repetitive, adaptive algorithms has the potential to be an effective rehabilitation medium to facilitate motor recovery of hand function. These findings are in accordance with current neuroscience literature in animals and motor control literature in humans. The investigators are now in a position to refine and optimize elements of the training paradigms to enhance neuroplasticity. The investigators first aim tests if and how competition among body parts for neural representations stifles functional gains from different types of training regimens. The second aim tests the functional benefits of unilateral versus bilateral training regimens.The third aim tests whether functional improvements gained from training in a virtual environment transfer to other (untrained) skills in the real world.

The complexity of sensorimotor control required for hand function as well as the wide range of recovery of manipulative abilities makes rehabilitation of the hand most challenging. The investigators past work has shown that training in a virtual environment (VE) using repetitive, adaptive algorithms has the potential to be an effective rehabilitation medium to facilitate motor recovery of hand function. These findings are in accordance with current neuroscience literature in animals and motor control literature in humans. The investigators are now in a position to refine and optimize elements of the training paradigms to enhance neuroplasticity. The investigators first aim tests if and how competition among body parts for neural representations stifles functional gains from different types of training regimens. The second aim tests the functional benefits of unilateral versus bilateral training regimens.The third aim tests whether functional improvements gained from training in a virtual environment transfer to other (untrained) skills in the real world.

Eight three hour training sessions of robotically facilitated hand and arm training in complex virtual environments, using activities that train the fingers in isolation and other activities that train the arm in isolation.

Robotically measured and facilitated training of the hemiparetic hand and arm in isolation, in a three dimensional haptically rendered virtual environment.

Robotically measured and facilitated training of the hemiparetic hand and arm as an integrated functional unit, in a three dimensional haptically rendered virtual environment

Robotically measured and facilitated training of the hemiparetic hand and non-hemiparetic hand together, in a three dimensional haptically rendered virtual environment

Two Weeks Prior to Training, Immediately Prior to Training, Immediately After Training, 3 Months After Training

Two Weeks Prior to Training, Immediately Prior to Training, Immediately After Training, 3 Months After Training

Two Weeks Prior to Training, Immediately Prior to Training, Immediately After Training, 3 Months After Training

Two Weeks Prior to Training, Immediately Prior to Training, Immediately After Training, 3 Months After Training

Inclusion Criteria: Six months post cerebrovascular accident Residual upper extremity impairment that affects participation At least ten degrees of active finger extension Tolerate passive shoulder flexion to chest level Exclusion Criteria: Severe neglect Severe aphasia

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