Welcome to the InfoSci Platform
SEMG for Human Computer Interface Using Ann to Navigate Wheel Chair

SEMG for Human Computer Interface Using Ann to Navigate Wheel Chair

V. Rajesh, P. Rajesh Kumar
Copyright: © 2012 |Pages: 8
ISBN13: 9781466617551|ISBN10: 1466617551|EISBN13: 9781466617568
DOI: 10.4018/978-1-4666-1755-1.ch012
Cite Chapter Cite Chapter

MLA

Rajesh, V., and P. Rajesh Kumar. "SEMG for Human Computer Interface Using Ann to Navigate Wheel Chair." Advancing Technologies and Intelligence in Healthcare and Clinical Environments Breakthroughs, edited by Joseph Tan, IGI Global, 2012, pp. 180-187. https://doi.org/10.4018/978-1-4666-1755-1.ch012

APA

Rajesh, V. & Kumar, P. R. (2012). SEMG for Human Computer Interface Using Ann to Navigate Wheel Chair. In J. Tan (Ed.), Advancing Technologies and Intelligence in Healthcare and Clinical Environments Breakthroughs (pp. 180-187). IGI Global. https://doi.org/10.4018/978-1-4666-1755-1.ch012

Chicago

Rajesh, V., and P. Rajesh Kumar. "SEMG for Human Computer Interface Using Ann to Navigate Wheel Chair." In Advancing Technologies and Intelligence in Healthcare and Clinical Environments Breakthroughs, edited by Joseph Tan, 180-187. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-4666-1755-1.ch012

Export Reference

Mendeley
Favorite

Abstract

This paper presents an approach to identify hand gestures with muscle activity separated from electromyogram (EMG) using Back Propagation analysis with the goal of using hand gestures for human-computer interaction. While there are a number of previous reported works where EMG has been used to identify movement, the limitation of these works is that the systems are suitable for gross actions and when there is one prime-mover muscle involved. This paper reports overcoming the difficulty by using independent component analysis to separate muscle activity from different muscles and classified using back propagation neural networks. The experimental results show that the system was accurately able to identify the hand gesture using this technique (95%). The advantage of this system is that it is easy to train one to use it and can easily be implemented in real time.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.