By Topic

Development and Quantitative Performance Evaluation of a Noninvasive EMG Computer Interface

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)
Changmok Choi ; Mech. Eng. Dept., Korea Adv. Inst. of Sci. & Technol. (KAIST), Daejeon ; Micera, S. ; Carpaneto, J. ; Jung Kim

This paper describes a noninvasive electromyography (EMG) signal-based computer interface and a performance evaluation method based on Fittspsila law. The EMG signals induced by volitional wrist movements were acquired from four sites in the lower arm to extract userspsila intentions, and six classes of wrist movements were distinguished using an artificial neural network. Using the developed interface, a user can move the cursor, click buttons, and type text on a computer. The test setup was built to evaluate the developed interface, and the mouse was tested by five volunteers with intact limbs. The performance of the developed computer interface and the mouse was tested at 1.299 and 7.733 b/s, respectively, and these results were compared with the performance of a commercial noninvasive brain signal interface (0.386 b/s). The results show that the developed interface performed better than the commercial interface, but less satisfactorily than a computer mouse. Although some issues remain to be resolved, the developed EMG interface has the potential to help people with motor disabilities to access computers and Internet environments in a natural and intuitive manner.

Published in:

Biomedical Engineering, IEEE Transactions on  (Volume:56 ,  Issue: 1 )