Literature DB >> 20022326

Uncovering chaotic structure in mechanomyography signals of fatigue biceps brachii muscle.

Hong-Bo Xie1, Jing-Yi Guo, Yong-Ping Zheng.   

Abstract

The mechanomyography (MMG) signal reflects mechanical properties of limb muscles that undergo complex phenomena in different functional states. We undertook the study of the chaotic nature of MMG signals by referring to recent developments in the field of nonlinear dynamics. MMG signals were measured from the biceps brachii muscle of 5 subjects during fatigue of isometric contraction at 80% maximal voluntary contraction (MVC) level. Deterministic chaotic character was detected in all data by using the Volterra-Wiener-Korenberg model and noise titration approach. The noise limit, a power indicator of the chaos of fatigue MMG signals, was 22.20+/-8.73. Furthermore, we studied the nonlinear dynamic features of MMG signals by computing their correlation dimension D(2), which was 3.35+/-0.36 across subjects. These results indicate that MMG is a high-dimensional chaotic signal and support the use of the theory of nonlinear dynamics for analysis and modeling of fatigue MMG signals. Copyright 2009 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2009        PMID: 20022326     DOI: 10.1016/j.jbiomech.2009.11.035

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  5 in total

1.  The effect of accelerometer location on the classification of single-site forearm mechanomyograms.

Authors:  Natasha Alves; Ervin Sejdić; Bhupinder Sahota; Tom Chau
Journal:  Biomed Eng Online       Date:  2010-06-10       Impact factor: 2.819

2.  A systematic review of muscle activity assessment of the biceps brachii muscle using mechanomyography.

Authors:  Irsa Talib; Kenneth Sundaraj; Chee Kiang Lam; Sebastian Sundaraj
Journal:  J Musculoskelet Neuronal Interact       Date:  2018-12-01       Impact factor: 2.041

3.  Estimation of Knee Extension Force Using Mechanomyography Signals Based on GRA and ICS-SVR.

Authors:  Zebin Li; Lifu Gao; Wei Lu; Daqing Wang; Huibin Cao; Gang Zhang
Journal:  Sensors (Basel)       Date:  2022-06-20       Impact factor: 3.847

Review 4.  Mechanomyogram for muscle function assessment: a review.

Authors:  Md Anamul Islam; Kenneth Sundaraj; R Badlishah Ahmad; Nizam Uddin Ahamed
Journal:  PLoS One       Date:  2013-03-11       Impact factor: 3.240

5.  Novel pseudo-wavelet function for MMG signal extraction during dynamic fatiguing contractions.

Authors:  Mohammed Rashid Al-Mulla; Francisco Sepulveda
Journal:  Sensors (Basel)       Date:  2014-05-28       Impact factor: 3.576

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.