Literature DB >> 12002176

A multiple-layer finite-element model of the surface EMG signal.

Madeleine M Lowery1, Nikolay S Stoykov, Allen Taflove, Todd A Kuiken.   

Abstract

The effect of skin, muscle, fat, and bone tissue on simulated surface electromyographic (EMG) signals was examined using a finite-element model. The amplitude and frequency content of the surface potential were observed to increase when the outer layer of a homogeneous muscle model was replaced with highly resistive skin or fat tissue. The rate at which the surface potential decreased as the fiber was moved deeper within the muscle also increased. Similarly, the rate at which the surface potential decayed around the surface of the model, for a constant fiber depth, increased. When layers of subcutaneous fat of increasing thickness were then added to the model, EMG amplitude, frequency content, and the rate of decay of the surface EMG signal around the limb decreased, due to the increased distance between the electrodes and the active fiber. The influence of bone on the surface potential was observed to vary considerably, depending on its location. When located close to the surface of the volume conductor, the surface EMG signal between the bone and the source and directly over the bone increased, accompanied by a slight decrease on the side of the bone distal to the active fiber. The results emphasize the importance of distinguishing between the effects of material properties and the distance between source and electrode when considering the influence of subcutaneous tissue, and suggest possible distortions in the surface EMG signal in regions where a bone is located close to the skin surface.

Mesh:

Year:  2002        PMID: 12002176     DOI: 10.1109/10.995683

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


  19 in total

1.  Influence of the subcutaneous fat layer, as measured by ultrasound, skinfold calipers and BMI, on the EMG amplitude.

Authors:  C Nordander; J Willner; G-A Hansson; B Larsson; J Unge; L Granquist; S Skerfving
Journal:  Eur J Appl Physiol       Date:  2003-04-24       Impact factor: 3.078

Review 2.  Surface electromyogram signal modelling.

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

3.  Advances in surface electromyographic signal simulation with analytical and numerical descriptions of the volume conductor.

Authors:  D Farina; L Mesin; S Martina
Journal:  Med Biol Eng Comput       Date:  2004-07       Impact factor: 2.602

4.  Predicting electromyographic signals under realistic conditions using a multiscale chemo-electro-mechanical finite element model.

Authors:  Mylena Mordhorst; Thomas Heidlauf; Oliver Röhrle
Journal:  Interface Focus       Date:  2015-04-06       Impact factor: 3.906

5.  Targeted Muscle Reinnervation for the Upper and Lower Extremity.

Authors:  Todd A Kuiken; Ann K Barlow; Levi Hargrove; Gregorgy A Dumanian
Journal:  Tech Orthop       Date:  2017-06

6.  Global Innervation Zone Identification With High-Density Surface Electromyography.

Authors:  Chuan Zhang; Nicholas Dias; Jinbao He; Ping Zhou; Sheng Li; Yingchun Zhang
Journal:  IEEE Trans Biomed Eng       Date:  2019-05-30       Impact factor: 4.538

7.  Targeted muscle reinnervation and advanced prosthetic arms.

Authors:  Jennifer E Cheesborough; Lauren H Smith; Todd A Kuiken; Gregory A Dumanian
Journal:  Semin Plast Surg       Date:  2015-02       Impact factor: 2.314

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

Authors:  Vincent Carriou; Sofiane Boudaoud; Jeremy Laforet
Journal:  Med Biol Eng Comput       Date:  2018-01-23       Impact factor: 2.602

9.  Three-Dimensional Innervation Zone Imaging from Multi-Channel Surface EMG Recordings.

Authors:  Yang Liu; Yong Ning; Sheng Li; Ping Zhou; William Z Rymer; Yingchun Zhang
Journal:  Int J Neural Syst       Date:  2015-09       Impact factor: 5.866

10.  Modeling of prosthetic limb rotation control by sensing rotation of residual arm bone.

Authors:  Guanglin Li; Todd A Kuiken
Journal:  IEEE Trans Biomed Eng       Date:  2008-09       Impact factor: 4.538

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