Literature DB >> 20535575

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

Javier Navallas1, Armando Malanda, Luis Gila, Javier Rodríguez, Ignacio Rodríguez.   

Abstract

The aim of this study was to develop a muscle architecture model able to account for the observed distributions of innervation ratios and fiber densities of different types of motor units in a muscle. A model algorithm is proposed and mathematically analyzed in order to obtain an inverse procedure that allows, by modification of input parameters, control over the output distributions of motor unit fiber densities. The model's performance was tested with independent data from a glycogen depletion study of the medial gastrocnemius of the rat. Results show that the model accurately reproduces the observed physiological distributions of innervation ratios and fiber densities and their relationships. The reliability and accuracy of the new muscle architecture model developed here can provide more accurate models for the simulation of different electromyographic signals.

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Year:  2010        PMID: 20535575     DOI: 10.1007/s11517-010-0642-x

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  61 in total

Review 1.  Scanning electromyography.

Authors:  Peter Diószeghy
Journal:  Muscle Nerve Suppl       Date:  2002

2.  Surface detected potentials of normal and reinnervated motor units: a simulation study for muscles consisted of short fibres.

Authors:  N A Dimitrova; C Disselhorst-Klug; A Trachterna; G V Dimitrov; G Rau
Journal:  Electromyogr Clin Neurophysiol       Date:  2002-06

3.  The presence of unknown layer of skin and fat is an obstacle to a correct estimation of the motor unit size from surface detected potentials.

Authors:  G V Dimitrov; C Disselhorst-Klug; N A Dimitrova; A Trachterna; G Rau
Journal:  Electromyogr Clin Neurophysiol       Date:  2002-06

4.  Causes of the increased fiber density in muscular dystrophies studied with single fiber EMG during electrical stimulation.

Authors:  P Hilton-Brown; E Stålberg; J Trontelj; M Mihelin
Journal:  Muscle Nerve       Date:  1985-06       Impact factor: 3.217

5.  Estimating motor unit discharge patterns from high-density surface electromyogram.

Authors:  Ales Holobar; Dario Farina; Marco Gazzoni; Roberto Merletti; Damjan Zazula
Journal:  Clin Neurophysiol       Date:  2009-02-08       Impact factor: 3.708

6.  Self-reinnervated cat medial gastrocnemius muscles. I. comparisons of the capacity for regenerating nerves to form enlarged motor units after extensive peripheral nerve injuries.

Authors:  V F Rafuse; T Gordon
Journal:  J Neurophysiol       Date:  1996-01       Impact factor: 2.714

7.  Motor unit size estimation of enlarged motor units with surface electromyography.

Authors:  K Roeleveld; A Sandberg; E V Stålberg; D F Stegeman
Journal:  Muscle Nerve       Date:  1998-07       Impact factor: 3.217

8.  Scanning EMG in normal muscle and in neuromuscular disorders.

Authors:  E Stålberg; P Dioszeghy
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1991-12

9.  Terminal innervation ratio in neuromuscular disease. I. Methods and controls.

Authors:  C Coërs; N Telerman-Toppet; J M Gérard
Journal:  Arch Neurol       Date:  1973-10

10.  On the measurement of fibre density in human muscles.

Authors:  I Gath; E Stålberg
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1982-12
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  3 in total

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

Authors:  Sridhar Poosapadi Arjunan; Dinesh Kant Kumar; Katherine Wheeler; Hirokazu Shimada; Ariba Siddiqi
Journal:  Med Biol Eng Comput       Date:  2015-07-30       Impact factor: 2.602

2.  Modifying motor unit territory placement in the Fuglevand model.

Authors:  Jason W Robertson; Jamie A Johnston
Journal:  Med Biol Eng Comput       Date:  2017-04-08       Impact factor: 2.602

3.  A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings.

Authors:  Íñigo Corera; Adrián Eciolaza; Oliver Rubio; Armando Malanda; Javier Rodríguez-Falces; Javier Navallas
Journal:  Med Biol Eng Comput       Date:  2018-01-11       Impact factor: 2.602

  3 in total

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