Literature DB >> 29359257

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

Vincent Carriou1, Sofiane Boudaoud2, Jeremy Laforet2.   

Abstract

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.

Entities:  

Keywords:  Computation time; HD-sEMG model; Motor unit electrical source; Optimization; Upscaling

Mesh:

Year:  2018        PMID: 29359257     DOI: 10.1007/s11517-018-1784-5

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


  21 in total

1.  A novel approach for precise simulation of the EMG signal detected by surface electrodes.

Authors:  D Farina; R Merletti
Journal:  IEEE Trans Biomed Eng       Date:  2001-06       Impact factor: 4.538

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Authors:  K Roeleveld; J H. Blok; D F. Stegeman; A van Oosterom
Journal:  J Electromyogr Kinesiol       Date:  1997-12       Impact factor: 2.368

3.  Three-layer volume conductor model and software package for applications in surface electromyography.

Authors:  J H Blok; D F Stegeman; A van Oosterom
Journal:  Ann Biomed Eng       Date:  2002-04       Impact factor: 3.934

4.  Muscle fiber number in the biceps brachii muscle of young and old men.

Authors:  Cliff S Klein; Greg D Marsh; Robert J Petrella; Charles L Rice
Journal:  Muscle Nerve       Date:  2003-07       Impact factor: 3.217

5.  A surface EMG generation model with multilayer cylindrical description of the volume conductor.

Authors:  Dario Farina; Luca Mesin; Simone Martina; Roberto Merletti
Journal:  IEEE Trans Biomed Eng       Date:  2004-03       Impact factor: 4.538

6.  Precise and fast calculation of the motor unit potentials detected by a point and rectangular plate electrode.

Authors:  G V Dimitrov; N A Dimitrova
Journal:  Med Eng Phys       Date:  1998-07       Impact factor: 2.242

7.  Realistic motor unit placement in a cylindrical HD-sEMG generation model.

Authors:  Vincent Carriou; Jeremy Laforet; Sofiane Boudaoud; Mariam Al Harrach
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2016-08

8.  Evaluation of muscle force classification using shape analysis of the sEMG probability density function: a simulation study.

Authors:  F S Ayachi; S Boudaoud; C Marque
Journal:  Med Biol Eng Comput       Date:  2014-06-25       Impact factor: 2.602

9.  Fast generation model of high density surface EMG signals in a cylindrical conductor volume.

Authors:  Vincent Carriou; Sofiane Boudaoud; Jeremy Laforet; Fouaz Sofiane Ayachi
Journal:  Comput Biol Med       Date:  2016-05-05       Impact factor: 4.589

10.  Models of recruitment and rate coding organization in motor-unit pools.

Authors:  A J Fuglevand; D A Winter; A E Patla
Journal:  J Neurophysiol       Date:  1993-12       Impact factor: 2.714

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