By Topic

Upper-Extremity Stroke Therapy Task Discrimination Using Motion Sensors and Electromyography

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

4 Author(s)
Giuffrida, J.P. ; Cleveland Med. Devices Inc., Cleveland ; Lerner, A. ; Steiner, R. ; Daly, J.

Brain injury resulting from stroke often causes upper-extremity motor deficits that limit activities of daily living. Several therapies being developed for motor rehabilitation after stroke focus on increasing time spent using the extremity to promote motor relearning. Providing a novel system for user-worn therapy may increase the amount and rate of functional motor recovery. A user-worn system comprising accelerometers, gyroscopes, and electromyography amplifiers was used to wirelessly transmit motion and muscle activity from normal and stroke subjects to a computer as they completed five upper-extremity rehabilitation tasks. An algorithm was developed to automatically detect the therapy task a subject performed based on the gyroscope and electromyography data. The system classified which task a subject was attempting to perform with greater than 80% accuracy despite the fact that those with severe impairment produced movements that did not resemble the goal tasks and were visually indistinguishable from different tasks. This developed system could potentially be used for home-therapy compliance monitoring, real-time patient feedback and to control therapy interventions.

Published in:

Neural Systems and Rehabilitation Engineering, IEEE Transactions on  (Volume:16 ,  Issue: 1 )