Literature DB >> 8324186

The bioelectrical source in computing single muscle fiber action potentials.

B K van Veen1, H Wolters, W Wallinga, W L Rutten, H B Boom.   

Abstract

Generally, single muscle fiber action potentials (SFAPs) are modeled as a convolution of the bioelectrical source (being the transmembrane current) with a weighting or transfer function, representing the electrical volume conduction. In practice, the intracellular action potential (IAP) rather than the transmembrane current is often used as the source, because the IAP is relatively easy to obtain under experimental conditions. Using a core conductor assumption, the transmembrane current equals the second derivative of the IAP. In previous articles, discrepancies were found between experimental and simulated SFAPs. Adaptations in the volume conductor slightly altered the simulation results. Another origin of discrepancy might be an erroneous description of the source. Therefore, in the present article, different sources were studied. First, an analytical description of the IAP was used. Furthermore, an experimental IAP, a special experimental SFAP, and a measured transmembrane current scaled to our experimental situation were applied. The results for the experimental IAP were comparable to those with the analytical IAP. The best agreement between experimental and simulated data was found for a measured transmembrane current as source, but differences are still apparent.

Mesh:

Year:  1993        PMID: 8324186      PMCID: PMC1262474          DOI: 10.1016/S0006-3495(93)81516-9

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  24 in total

1.  Potential distribution and single-fibre action potentials in a radially bounded muscle model.

Authors:  B K van Veen; N J Rijkhoff; W L Rutten; W Wallinga; H B Boom
Journal:  Med Biol Eng Comput       Date:  1992-05       Impact factor: 2.602

2.  Power spectra of extracellular potentials generated by an infinite, homogeneous excitable fibre.

Authors:  G V Dimitrov; Z C Lateva; N A Dimitrova
Journal:  Med Biol Eng Comput       Date:  1990-01       Impact factor: 2.602

3.  Effects of changes in asymmetry, duration and propagation velocity of the intracellular potential on the power spectrum of extracellular potentials produced by an excitable fiber.

Authors:  G V Dimitrov; Z C Lateva; N A Dimitrova
Journal:  Electromyogr Clin Neurophysiol       Date:  1988 Mar-Apr

4.  The active fiber in a volume conductor.

Authors:  R Plonsey
Journal:  IEEE Trans Biomed Eng       Date:  1974-09       Impact factor: 4.538

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Authors:  M S Spach; R C Barr; G A Serwer; J M Kootsey; E A Johnson
Journal:  Circ Res       Date:  1972-05       Impact factor: 17.367

6.  Intra- and extracellular potential fields of active nerve and muscle fibres. A physico-mathematical analysis of different models.

Authors:  P Rosenfalck
Journal:  Acta Physiol Scand Suppl       Date:  1969

7.  The extracellular potential field of the single active nerve fiber in a volume conductor.

Authors:  J Clark; R Plonsey
Journal:  Biophys J       Date:  1968-07       Impact factor: 4.033

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Authors:  P A Griep; F L Gielen; H B Boom; K L Boon; L L Hoogstraten; C W Pool; W Wallinga-De Jonge
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1982-04

Review 9.  Relationship of intracellular and extracellular action potentials of skeletal muscle fibers.

Authors:  S Andreassen; A Rosenfalck
Journal:  Crit Rev Bioeng       Date:  1981-11

10.  A mathematical evaluation of the core conductor model.

Authors:  J Clark; R Plonsey
Journal:  Biophys J       Date:  1966-01       Impact factor: 4.033

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  9 in total

Review 1.  Surface electromyogram signal modelling.

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

2.  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

3.  Effect of number of motor units and muscle fibre type on surface electromyogram.

Authors:  Sridhar Poosapadi Arjunan; Dinesh Kant Kumar; Katherine Wheeler; Hirokazu Shimada; Ariba Siddiqi
Journal:  Med Biol Eng Comput       Date:  2015-07-30       Impact factor: 2.602

4.  Influence of inhomogeneities in muscle tissue on single-fibre action potentials: a model study.

Authors:  W L Rutten; B K van Veen; S H Stroeve; H B Boom; W Wallinga
Journal:  Med Biol Eng Comput       Date:  1997-03       Impact factor: 2.602

5.  Muscle electric activity. II: On the feasibility of model-based estimation of experimental conditions in electromyography.

Authors:  T H Gootzen; D F Stegeman; A van Oosterom
Journal:  Ann Biomed Eng       Date:  1993 Jul-Aug       Impact factor: 3.934

6.  Motor unit innervation zone localization based on robust linear regression analysis.

Authors:  Jie Liu; Sheng Li; Faezeh Jahanmiri-Nezhad; William Zev Rymer; Ping Zhou
Journal:  Comput Biol Med       Date:  2019-01-14       Impact factor: 4.589

7.  Decomposition of fractionated local electrograms using an analytic signal model based on sigmoid functions.

Authors:  Thomas Wiener; Fernando O Campos; Gernot Plank; Ernst Hofer
Journal:  Biomed Tech (Berl)       Date:  2012-10       Impact factor: 1.411

8.  An Empirical Muscle Intracellular Action Potential Model with Multiple Erlang Probability Density Functions based on a Modified Newton Method.

Authors:  Gyutae Kim; Mohammed M Ferdjallah; Frederic D McKenzie
Journal:  Biomed Eng Comput Biol       Date:  2013-04-14

9.  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

  9 in total

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