Next Article in Journal
Minimum Entropy Active Fault Tolerant Control of the Non-Gaussian Stochastic Distribution System Subjected to Mean Constraint
Next Article in Special Issue
Investigation of the Intra- and Inter-Limb Muscle Coordination of Hands-and-Knees Crawling in Human Adults by Means of Muscle Synergy Analysis
Previous Article in Journal
A Functorial Construction of Quantum Subtheories
Previous Article in Special Issue
Acoustic Detection of Coronary Occlusions before and after Stent Placement Using an Electronic Stethoscope
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle
Entropy 2017, 19(5), 221; doi:10.3390/e19050221

Muscle Fatigue Analysis of the Deltoid during Three Head-Related Static Isometric Contraction Tasks

Department of Electronic Science and Technology, University of Science and Technology of China, Hefei 230026, China
*
Author to whom correspondence should be addressed.
Academic Editors: Danilo P. Mandic, Andrzej Cichocki and Chung-Kang Peng
Received: 27 March 2017 / Revised: 5 May 2017 / Accepted: 9 May 2017 / Published: 11 May 2017
(This article belongs to the Special Issue Information Theory Applied to Physiological Signals)
View Full-Text   |   Download PDF [2200 KB, uploaded 11 May 2017]   |  

Abstract

This study aimed to investigate the fatiguing characteristics of muscle-tendon units (MTUs) within skeletal muscles during static isometric contraction tasks. The deltoid was selected as the target muscle and three head-related static isometric contraction tasks were designed to activate three heads of the deltoid in different modes. Nine male subjects participated in this study. Surface electromyography (SEMG) signals were collected synchronously from the three heads of the deltoid. The performances of five SEMG parameters, including root mean square (RMS), mean power frequency (MPF), the first coefficient of autoregressive model (ARC1), sample entropy (SE) and Higuchi’s fractal dimension (HFD), in quantification of fatigue, were evaluated in terms of sensitivity to variability ratio (SVR) and consistency firstly. Then, the HFD parameter was selected as the fatigue index for further muscle fatigue analysis. The experimental results demonstrated that the three deltoid heads presented different activation modes during three head-related fatiguing contractions. The fatiguing characteristics of the three heads were found to be task-dependent, and the heads kept in a relatively high activation level were more prone to fatigue. In addition, the differences in fatiguing rate between heads increased with the increase in load. The findings of this study can be helpful in better understanding the underlying neuromuscular control strategies of the central nervous system (CNS). Based on the results of this study, the CNS was thought to control the contraction of the deltoid by taking the three heads as functional units, but a certain synergy among heads might also exist to accomplish a contraction task. View Full-Text
Keywords: muscle fatigue; deltoid; SEMG; MTUs; static isometric contraction muscle fatigue; deltoid; SEMG; MTUs; static isometric contraction
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Cui, W.; Chen, X.; Cao, S.; Zhang, X. Muscle Fatigue Analysis of the Deltoid during Three Head-Related Static Isometric Contraction Tasks. Entropy 2017, 19, 221.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top