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

A muscular fatigue index based on the relationships between superimposed M wave and preceding background activity

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)
Kiryu, T. ; Graduate Sch. of Sci. & Technol., Niigata Univ., Japan ; Morishiata, M. ; Yamada, H. ; Okada, M.

A practical muscle fatigue index is studied in this paper using the correlation between the instantaneous frequencies (IF's) of the superimposed M wave and the mean power frequency (MPF) of the preceding background activity. A superimposed M wave is an M wave elicited during a sustained contraction and was recently introduced for studying muscle fatigue. The authors investigated the details of the distribution of a feature vector (mpf, if) in two-dimensional space. Their experimental results showed that MPF and IF's were closely correlated during the first phase of a short-term high-level sustained voluntary contraction and then became uncorrelated or sometimes showed negative correlation as muscular fatigue progressed. Combining the correlation coefficients and conventional myoelectric (ME) parameters, such as the MPF and the average rectified value of ME signals, the authors propose a fuzzy rule based muscular fatigue index that can be used for managing the inevitable variability among individual subjects collected as a group. Introducing fuzzy inference seemed effective, but further studies including detailed investigation of the level of voluntary effort, the muscle fiber type composition, and metabolic by-products will be needed to customize the membership functions and fuzzy rules more appropriately in each practical field.

Published in:

Biomedical Engineering, IEEE Transactions on  (Volume:45 ,  Issue: 10 )

Date of Publication:

Oct. 1998

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.