Literature DB >> 16602565

A finite element model for describing the effect of muscle shortening on surface EMG.

Luca Mesin1, Michelle Joubert, Tania Hanekom, Roberto Merletti, Dario Farina.   

Abstract

A finite-element model for the generation of single fiber action potentials in a muscle undergoing various degrees of fiber shortening is developed. The muscle is assumed fusiform with muscle fibers following a curvilinear path described by a Gaussian function. Different degrees of fiber shortening are simulated by changing the parameters of the fiber path and maintaining the volume of the muscle constant. The conductivity tensor is adapted to the muscle fiber orientation. In each point of the volume conductor, the conductivity of the muscle tissue in the direction of the fiber is larger than that in the transversal direction. Thus, the conductivity tensor changes point-by-point with fiber shortening, adapting to the fiber paths. An analytical derivation of the conductivity tensor is provided. The volume conductor is then studied with a finite-element approach using the analytically derived conductivity tensor. Representative simulations of single fiber action potentials with the muscle at different degrees of shortening are presented. It is shown that the geometrical changes in the muscle, which imply changes in the conductivity tensor, determine important variations in action potential shape, thus affecting its amplitude and frequency content. The model provides a new tool for interpreting surface EMG signal features with changes in muscle geometry, as it happens during dynamic contractions.

Mesh:

Year:  2006        PMID: 16602565     DOI: 10.1109/TBME.2006.870256

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  7 in total

1.  Effects of muscle fibre shortening on the characteristics of surface motor unit potentials.

Authors:  Javier Rodriguez-Falces; Nicolas Place
Journal:  Med Biol Eng Comput       Date:  2013-10-30       Impact factor: 2.602

2.  Influence of inter-electrode distance, contraction type, and muscle on the relationship between the sEMG power spectrum and contraction force.

Authors:  Javier Rodriguez-Falces; Daria Neyroud; Nicolas Place
Journal:  Eur J Appl Physiol       Date:  2014-11-21       Impact factor: 3.078

3.  Predicting electromyographic signals under realistic conditions using a multiscale chemo-electro-mechanical finite element model.

Authors:  Mylena Mordhorst; Thomas Heidlauf; Oliver Röhrle
Journal:  Interface Focus       Date:  2015-04-06       Impact factor: 3.906

4.  Anatomically accurate model of EMG during index finger flexion and abduction derived from diffusion tensor imaging.

Authors:  Diego Pereira Botelho; Kathleen Curran; Madeleine M Lowery
Journal:  PLoS Comput Biol       Date:  2019-08-29       Impact factor: 4.475

5.  Effects of muscle shortening on single-fiber, motor unit, and compound muscle action potentials.

Authors:  Javier Rodriguez-Falces; Armando Malanda; Javier Navallas
Journal:  Med Biol Eng Comput       Date:  2021-12-22       Impact factor: 2.602

6.  An Empirical Muscle Intracellular Action Potential Model with Multiple Erlang Probability Density Functions based on a Modified Newton Method.

Authors:  Gyutae Kim; Mohammed M Ferdjallah; Frederic D McKenzie
Journal:  Biomed Eng Comput Biol       Date:  2013-04-14

7.  A Finite Element Model Approach to Determine the Influence of Electrode Design and Muscle Architecture on Myoelectric Signal Properties.

Authors:  A Teklemariam; E F Hodson-Tole; N D Reeves; N P Costen; G Cooper
Journal:  PLoS One       Date:  2016-02-17       Impact factor: 3.240

  7 in total

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