Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 12:00 PM ET (12:00 - 16:00 UTC). We apologize for the inconvenience.
By Topic

VR Aided Motor Training for Post-Stroke Rehabilitation: System Design, Clinical Test, Methodology for Evaluation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Shih-Ching Yeh ; Dept. of Comput. Sci., Southern California Univ., Los Angeles, CA ; Stewart, J. ; McLaughlin, M. ; Parsons, T.
more authors

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: pre-training, 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.

Published in:

Virtual Reality Conference, 2007. VR '07. IEEE

Date of Conference:

10-14 March 2007