Literature DB >> 10721626

A model of EMG generation.

J Duchêne1, J Y Hogrel.   

Abstract

Simulation models are unavoidable in experimental research when the point is to develop new processing algorithms to be applied on real signals in order to extract specific parameter values. Such algorithms have generally to be optimized by comparing true parameter values to those deduced from the algorithm. Only a simulation model can allow the user to access and control the actual process parameter values. This constraint is especially true when dealing with biomedical signals like surface electromyogram (SEMG). This work is an attempt to produce an efficient SEMG simulation model as a help for assessing algorithms related to SEMG features description. It takes into account the most important parameters which could influence these characteristics. This model includes all transformations from intracellular potential to surface recordings as well as a fast implementation of the extracellular potential computation. In addition, this model allows multiple graphically-programmable electrode-set configurations and SEMG simulation in both voluntary and elicited contractions.

Mesh:

Year:  2000        PMID: 10721626     DOI: 10.1109/10.821754

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


  16 in total

1.  Motor unit conduction velocity distribution estimation: assessment of two short-term processing methods.

Authors:  J Y Hogrel; J Duchêne
Journal:  Med Biol Eng Comput       Date:  2002-03       Impact factor: 2.602

2.  Automatic identification of motor unit action potential trains from electromyographic signals using fuzzy techniques.

Authors:  E Chauvet; O Fokapu; J Y Hogrel; D Gamet; J Duchêne
Journal:  Med Biol Eng Comput       Date:  2003-11       Impact factor: 2.602

Review 3.  Surface electromyogram signal modelling.

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

4.  Influence of the shape of intracellular potentials on the morphology of single-fiber extracellular potentials in human muscle fibers.

Authors:  Javier Rodriguez-Falces; Javier Navallas; Luis Gila; Armando Malanda; Nonna Alexandrovna Dimitrova
Journal:  Med Biol Eng Comput       Date:  2012-03-24       Impact factor: 2.602

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

Authors:  Javier Navallas; Armando Malanda; Luis Gila; Javier Rodríguez; Ignacio Rodríguez
Journal:  Med Biol Eng Comput       Date:  2010-06-10       Impact factor: 2.602

6.  Comparative evaluation of motor unit architecture models.

Authors:  Javier Navallas; Armando Malanda; Luis Gila; Javier Rodriguez; Ignacio Rodriguez
Journal:  Med Biol Eng Comput       Date:  2009-08-25       Impact factor: 2.602

7.  A Novel Framework Based on FastICA for High Density Surface EMG Decomposition.

Authors:  Maoqi Chen; Ping Zhou
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2015-03-11       Impact factor: 3.802

8.  Nonhomogeneous volume conduction effects affecting needle electromyography: an analytical and simulation study.

Authors:  Xuesong Luo; Shaoping Wang; Seward B Rutkove; Benjamin Sanchez
Journal:  Physiol Meas       Date:  2021-12-28       Impact factor: 2.833

9.  Calculation of spatially filtered signals produced by a motor unit comprising muscle fibres with non-uniform propagation.

Authors:  N A Dimitrova; G V Dimitrov; A G Dimitrov
Journal:  Med Biol Eng Comput       Date:  2001-03       Impact factor: 3.079

10.  Model-Based Analysis of Muscle Strength and EMG-Force Relation with respect to Different Patterns of Motor Unit Loss.

Authors:  Chengjun Huang; Maoqi Chen; Yingchun Zhang; Sheng Li; Ping Zhou
Journal:  Neural Plast       Date:  2021-06-22       Impact factor: 3.599

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