Cart (Loading....) | Create Account
Close category search window
 

Electromyogram (EMG) feature reduction using Mutual Components Analysis for multifunction prosthetic fingers control

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

2 Author(s)
Khushaba, R.N. ; Sch. of Electr., Mech., & Mechatron. Syst., Univ. of Technol., Sydney (UTS), Sydney, NSW, Australia ; Kodagoda, S.

Surface Electromyogram (EMG) signals are usually utilized as a control source for multifunction powered prostheses. A challenge that arises with the current demands of such prostheses is the ability to accurately control a large number of individual and combined fingers movements and to do so in a computationally efficient manner. As a response to such a challenge, we present a combined feature selection and projection algorithm, denoted as Mutual Components Analysis (MCA). The proposed MCA algorithm extends the well-known Principal Components Analysis (PCA) by pruning the noisy and redundant features before projecting the data. To implement the feature selection step, the mutual information concept is utilized to implement a new information gain evaluation function. The performance and significance of the proposed MCA is demonstrated on EMG datasets collected for the purpose of this research from eight subjects with eight electrodes attached on their forearm. Fifteen classes of fingers movements where considered in this paper with MCA achieving >95% accuracy on average across all subjects.

Published in:

Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on

Date of Conference:

5-7 Dec. 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.