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2007 IEEE Virtual Reality Conference
VR Aided Motor Training for Post-Stroke Rehabilitation: System Design, Clinical Test, Methodology for Evaluation
Charlotte, NC, USA
March 10-March 14
ISBN: 1-4244-0905-5
Shih-Ching Yeh, Department of Computer Science, University of Southern California, Los Angeles, CA
Jill Stewart, Department of Biokinesiology&Physical Therapy, University of Southern California, Los Angeles, CA
Margaret McLaughlin, Annenberg School for Communication, University of Southern California, Los Angeles, CA
Thomas Parsons, Institute for Creative Technologies, University of Southern California, Los Angeles, CA
Carolee J. Winstein, Department of Biokinesiology&Physical Therapy, University of Southern California, Los Angeles, CA
Albert Rizzo, Institute for Creative Technologies, University of Southern California, Los Angeles, CA
This paper describes interdisciplinary work on developing a virtual reality (VR) aided motor training task for post-stroke rehabilitation on functional deficits of the upper extremity: static reaching. Patient-specific and human-centered design of the VR system was addressed from the physical therapist's perspective. The two main features of the system were that it could actively drive the human kinetic behavior based on the therapist's rehabilitation goals and capture the patient's kinetic performance in an accurate way. A three-month clinical trial of this VR task was conducted with five post-stroke patients. To analyze the collected data, a methodology was proposed to visualize the patient's current status and progression over time based on three kinematics measures: performance time, movement efficiency, and moving speed. Results from the analysis clearly reveal the current status of the patient's hand and arm movement with respect to his/her range of motion, comprising pitch, yaw and arm length. Further, evidence of progress was found and visualized quantitatively over a series of practice sessions. Along with several conventional behavioral assessments at three points: pretraining, mid-training and post-training, the patient's progress was identified as well. Finally, human factors, such as perception of difficulty, confidence of movement, and system usability, were measured and studied.
Citation:
Shih-Ching Yeh, Jill Stewart, Margaret McLaughlin, Thomas Parsons, Carolee J. Winstein, Albert Rizzo, "VR Aided Motor Training for Post-Stroke Rehabilitation: System Design, Clinical Test, Methodology for Evaluation," vr, pp.299-300, 2007 IEEE Virtual Reality Conference, 2007
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