Speedup computation of HD-sEMG signals using a motor unit-specific electrical source model.

Nowadays, bio-reliable modeling of muscle contraction is becoming more accurate and complex. This increasing complexity induces a significant increase in computation time which prevents the possibility of using this model in certain applications and studies. Accordingly, the aim of this work is to s...

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Publicado en:Medical & Biological Engineering & Computing Vol. 56; no. 8; pp. 1459 - 1474
Autores principales: Carriou, Vincent, Boudaoud, Sofiane, Laforet, Jeremy
Formato: equations & formulas pictorial research tables/charts Journal Article
Publicado: Springer Nature Aug2018
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2018
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      pub: Springer Nature
      place: New York, New York
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        atl: Speedup computation of HD-sEMG signals using a motor unit-specific electrical source model.
      aug:
        au:
          Carriou, Vincent
          Boudaoud, Sofiane
          Laforet, Jeremy
        affil: CNRS UMR 7338 Biomechanics and Bioengineering, Centre de Recherche de Royallieu, Sorbonne University, Universite de Technologie de Compiegne, CS 60203, Compiegne, France
      sug:
        subj:
          Motor Neurons Physiology
          Signal Processing, Computer Assisted
          Electricity
          Models, Biological
          Electromyography
          Time Factors
          Action Potentials Physiology
          Computer Simulation
          Human
      ab: Nowadays, bio-reliable modeling of muscle contraction is becoming more accurate and complex. This increasing complexity induces a significant increase in computation time which prevents the possibility of using this model in certain applications and studies. Accordingly, the aim of this work is to significantly reduce the computation time of high-density surface electromyogram (HD-sEMG) generation. This will be done through a new model of motor unit (MU)-specific electrical source based on the fibers composing the MU. In order to assess the efficiency of this approach, we computed the normalized root mean square error (NRMSE) between several simulations on single generated MU action potential (MUAP) using the usual fiber electrical sources and the MU-specific electrical source. This NRMSE was computed for five different simulation sets wherein hundreds of MUAPs are generated and summed into HD-sEMG signals. The obtained results display less than 2% error on the generated signals compared to the same signals generated with fiber electrical sources. Moreover, the computation time of the HD-sEMG signal generation model is reduced to about 90% compared to the fiber electrical source model. Using this model with MU electrical sources, we can simulate HD-sEMG signals of a physiological muscle (hundreds of MU) in less than an hour on a classical workstation. Graphical Abstract Overview of the simulation of HD-sEMG signals using the fiber scale and the MU scale. Upscaling the electrical source to the MU scale reduces the computation time by 90% inducing only small deviation of the same simulated HD-sEMG signals.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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