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

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 t...

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Publicado en:Medical & Biological Engineering & Computing Vol. 48; no. 9; pp. 875 - 887
Autores principales: Navallas J, Malanda A, Gila L, Rodríguez J, Rodríguez I, Navallas, Javier, Malanda, Armando, Gila, Luis, Rodríguez, Javier, Rodríguez, Ignacio
Formato: research Journal Article
Publicado: Springer Nature Sep2010
Acceso en línea:Ver este registro en EBSCOhost
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        atl: A muscle architecture model offering control over motor unit fiber density distributions.
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        au:
          Navallas J
          Malanda A
          Gila L
          Rodríguez J
          Rodríguez I
          Navallas, Javier
          Malanda, Armando
          Gila, Luis
          Rodríguez, Javier
          Rodríguez, Ignacio
        affil: Department of Electric and Electronic Engineering, Public University of Navarra, Pamplona, Navarra, Spain
      sug:
        subj:
          Models, Biological
          Motor Neurons
          Muscle, Skeletal
          Algorithms
          Electromyography Methods
          Motor Neurons Physiology
          Muscle, Skeletal Physiology
          Muscle, Skeletal Innervation
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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