Literature DB >> 15320455

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

D Farina1, L Mesin, S Martina.   

Abstract

Surface electromyographic (EMG) signal modelling is important for signal interpretation, testing of processing algorithms, detection system design and didactic purposes. Various surface EMG signal models have been proposed in the literature. This study focuses on the proposal of a method for modelling surface EMG signals, using either analytical or numerical descriptions of the volume conductor for space-invariant systems, and on the development of advanced models of the volume conductor by numerical approaches, accurately describing the volume conductor geometry and the conductivity, as mainly done in the past, but also the conductivity tensor of the muscle tissue. For volume conductors that are space-invariant in the direction of source propagation, the surface potentials generated by any source can be computed by one-dimensional convolutions, once the volume conductor transfer function has been derived (analytically or numerically). Conversely, more complex volume conductors require a complete numerical approach. In a numerical approach, the conductivity tensor of the muscle tissue should be matched with the fibre orientation. In some cases (e.g. multi-pinnate muscles), accurate description of the conductivity tensor can be very complex. A method for relating the conductivity tensor of the muscle tissue, to be used in a numerical approach, to the curve describing the muscle fibres is presented and applied to investigate representatively a bi-pinnate muscle with rectilinear and curvilinear fibres. The study thus proposes an approach for surface EMG signal simulation in space invariant systems, as well as new models of the volume conductor using numerical methods.

Mesh:

Year:  2004        PMID: 15320455     DOI: 10.1007/bf02350987

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


  34 in total

1.  Effect of electrode dimensions on motor unit potentials.

Authors:  N A Dimitrova; G V Dimitrov; V N Chikhman
Journal:  Med Eng Phys       Date:  1999 Jul-Sep       Impact factor: 2.242

2.  Influence of motoneuron firing synchronization on SEMG characteristics in dependence of electrode position.

Authors:  B U Kleine; D F Stegeman; D Mund; C Anders
Journal:  J Appl Physiol (1985)       Date:  2001-10

3.  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

4.  Volume conduction models for surface EMG; confrontation with measurements.

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

5.  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

6.  Reproducibility of muscle-fiber conduction velocity estimates using multichannel surface EMG techniques.

Authors:  Dario Farina; Domenico Zagari; Marco Gazzoni; Roberto Merletti
Journal:  Muscle Nerve       Date:  2004-02       Impact factor: 3.217

7.  Influence of tissue inhomogeneities on noninvasive muscle fiber conduction velocity measurements--investigated by physical and numerical modeling.

Authors:  J Schneider; J Silny; G Rau
Journal:  IEEE Trans Biomed Eng       Date:  1991-09       Impact factor: 4.538

8.  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

Review 9.  Interpretation of EMG changes with fatigue: facts, pitfalls, and fallacies.

Authors:  N A Dimitrova; G V Dimitrov
Journal:  J Electromyogr Kinesiol       Date:  2003-02       Impact factor: 2.368

10.  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

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  5 in total

Review 1.  Methods for estimating muscle fibre conduction velocity from surface electromyographic signals.

Authors:  D Farina; R Merletti
Journal:  Med Biol Eng Comput       Date:  2004-07       Impact factor: 2.602

2.  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

3.  Motor Unit Action Potential Clustering-Theoretical Consideration for Muscle Activation during a Motor Task.

Authors:  Michael J Asmussen; Vinzenz von Tscharner; Benno M Nigg
Journal:  Front Hum Neurosci       Date:  2018-01-31       Impact factor: 3.169

4.  Anatomically accurate model of EMG during index finger flexion and abduction derived from diffusion tensor imaging.

Authors:  Diego Pereira Botelho; Kathleen Curran; Madeleine M Lowery
Journal:  PLoS Comput Biol       Date:  2019-08-29       Impact factor: 4.475

5.  A computational model to investigate the effect of pennation angle on surface electromyogram of Tibialis Anterior.

Authors:  Diptasree Maitra Ghosh; Dinesh Kumar; Sridhar Poosapadi Arjunan; Ariba Siddiqi; Ramakrishnan Swaminathan
Journal:  PLoS One       Date:  2017-12-07       Impact factor: 3.240

  5 in total

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