Literature DB >> 10396899

Modeling of surface myoelectric signals--Part I: Model implementation.

R Merletti1, L Lo Conte, E Avignone, P Guglielminotti.   

Abstract

The relationships between the parameters of active motor units (MU's) and the features of surface electromyography (EMG) signals have been investigated using a mathematical model that represents the surface EMG as a summation of contributions from the single muscle fibers. Each MU has parallel fibers uniformly scattered within a cylindrical volume of specified radius embedded in an anisotropic medium. Two action potentials, each modeled as a current tripole, are generated at the neuromuscular junction, propagate in opposite directions and extinguish at the fiber-tendon endings. The neuromuscular junctions and fiber-tendon endings are uniformly scattered within regions of specified width. Muscle fiber conduction velocity and average fiber length to the right and left of the center of the innervation zone are also specified. The signal produced by MU's with different geometries and conduction velocities are superimposed. Monopolar, single differential and double differential signals are computed from electrodes placed in equally spaced locations on the surface of the muscle and are displayed as functions of any of the model's parameters. Spectral and amplitude variables and conduction velocity are estimated from the surface signals and displayed as functions of any of the model's parameters. The influence of fiber-end effects, electrode misalignment, tissue anisotropy, MU's location and geometry are discussed. Part II of this paper will focus on the simulation and interpretation of experimental signals.

Mesh:

Year:  1999        PMID: 10396899     DOI: 10.1109/10.771190

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


  31 in total

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Authors:  K C McGill
Journal:  Med Biol Eng Comput       Date:  2004-07       Impact factor: 2.602

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Journal:  Med Biol Eng Comput       Date:  2004-07       Impact factor: 2.602

3.  A muscle architecture model offering control over motor unit fiber density distributions.

Authors:  Javier Navallas; Armando Malanda; Luis Gila; Javier Rodríguez; Ignacio Rodríguez
Journal:  Med Biol Eng Comput       Date:  2010-06-10       Impact factor: 2.602

4.  Effect of number of motor units and muscle fibre type on surface electromyogram.

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Journal:  Med Biol Eng Comput       Date:  2015-07-30       Impact factor: 2.602

5.  Multiple-electrode nerve cuffs for low-velocity and velocity-selective neural recording.

Authors:  J Taylor; N Donaldson; J Winter
Journal:  Med Biol Eng Comput       Date:  2004-09       Impact factor: 2.602

6.  Ankle position and voluntary contraction alter maximal M waves in soleus and tibialis anterior.

Authors:  Alain Frigon; Timothy J Carroll; Kelvin E Jones; E Paul Zehr; David F Collins
Journal:  Muscle Nerve       Date:  2007-06       Impact factor: 3.217

7.  A simulation study for a surface EMG sensor that detects distinguishable motor unit action potentials.

Authors:  Jin Lee; Alexander Adam; Carlo J De Luca
Journal:  J Neurosci Methods       Date:  2007-09-18       Impact factor: 2.390

8.  Detecting the unique representation of motor-unit action potentials in the surface electromyogram.

Authors:  Dario Farina; Francesco Negro; Marco Gazzoni; Roger M Enoka
Journal:  J Neurophysiol       Date:  2008-05-21       Impact factor: 2.714

9.  Comparative evaluation of motor unit architecture models.

Authors:  Javier Navallas; Armando Malanda; Luis Gila; Javier Rodriguez; Ignacio Rodriguez
Journal:  Med Biol Eng Comput       Date:  2009-08-25       Impact factor: 2.602

10.  Back and hip extensor muscles fatigue in healthy subjects: task-dependency effect of two variants of the Sorensen test.

Authors:  Annick Champagne; Martin Descarreaux; Danik Lafond
Journal:  Eur Spine J       Date:  2008-09-24       Impact factor: 3.134

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