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dc.contributor.author Zahedi, Edmond en_US
dc.date.accessioned 2011-10-03T19:59:47Z
dc.date.available 2011-10-03T19:59:47Z
dc.date.issued 1995 en_US
dc.identifier.citation From "MEC 95," Proceedings of the 1995 MyoElectric Controls/Powered Prosthetics Symposium Fredericton, New Brunswick, Canada: August, 1995. Copyright University of New Brunswick. en_US
dc.identifier.uri http://hdl.handle.net/10161/4854
dc.description.abstract In this paper, a new approach is presented for the training of amputees for an effective fitting of upper-extremity myo-electric prostheses, Electromyogram (EMG) signals from the remaining muscles of the stump are amplified and filtered, digitized with 8 bit resolution and fed htro a microcomputer with a sampling rate of 2500 Hz, The extracted feature is the integral absolute value of the biceps and triceps. A fuzzy classifier is used for clustering and classification. The EMG signals are processed and the decision of the classifier animates a graphically simulated 3 degree of freedom prosthesis on the microcomputer monitor. Five healthy persons have been trained with this system It took less than 10 minutes for the subjects to familiarize with the operation of the system. The error rate was less than 5%. The main advantages of such an approach are thought to be: training of amputees before using a real prosthesis by remembering them the concept of "muscle state", easy evaluation of the misclassification error rate of different algorithms, expert man-power time saving, accurate follow-up of the amputee, more availability of the training set and self-paced learning so less frustration of the amputee. en_US
dc.publisher Myoelectric Symposium en_US
dc.subject Electromyogram (EMG) en_US
dc.subject Artificial hand en_US
dc.subject Computer graphics en_US
dc.title A New Approach To Amputee Training Using Computer Graphics en_US

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