Literature DB >> 9136199

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

W L Rutten1, B K van Veen, S H Stroeve, H B Boom, W Wallinga.   

Abstract

The influence of changes in electrical conductivity, due to the muscle boundary, layers and compartments of intramuscular connective tissue and blood vessels, on computed single-muscle fibre action potentials (SFAPs) in rat hindleg muscle is calculated. The position of the active fibre is varied throughout the muscle. For fibres close to the muscle boundary, peak-to-peak voltages of SFAPs increase by up to a factor of 3 compared with the unbounded situation. For inner fibres, the presence of nearby connective tissue compartments causes an increase of up to 40%. A blood vessel in the neighbourhood of the active fibre leads to a decrease of at most 20%, for recording sites between the active fibre and the blood vessel. For recording sites beyond the blood vessel, peak-to-peak voltages increase by up to 20%.

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Year:  1997        PMID: 9136199     DOI: 10.1007/bf02534136

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


  19 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.  Influence of a frequency-dependent medium around a network model, used for the simulation of single-fibre action potentials.

Authors:  B K van Veen; W L Rutten; W Wallinga
Journal:  Med Biol Eng Comput       Date:  1990-09       Impact factor: 2.602

3.  Single fibre action potentials in skeletal muscle related to recording distances.

Authors:  B K van Veen; E Mast; R Busschers; A J Verloop; W Wallinga; W L Rutten; P O Gerrits; H B Boom
Journal:  J Electromyogr Kinesiol       Date:  1994       Impact factor: 2.368

4.  Quantitative analysis of single muscle fibre action potentials recorded at known distances.

Authors:  B A Albers; J H Put; W Wallinga; P Wirtz
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1989-09

5.  Sensitivity of the amplitude of the single muscle fibre action potential to microscopic volume conduction parameters.

Authors:  B A Albers; W L Rutten; W Wallinga-de Jonge; H B Boom
Journal:  Med Biol Eng Comput       Date:  1988-11       Impact factor: 2.602

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.  Model of electrical conductivity of skeletal muscle based on tissue structure.

Authors:  F L Gielen; H E Cruts; B A Albers; K L Boon; W Wallinga-de Jonge; H B Boom
Journal:  Med Biol Eng Comput       Date:  1986-01       Impact factor: 2.602

8.  The bioelectrical source in computing single muscle fiber action potentials.

Authors:  B K van Veen; H Wolters; W Wallinga; W L Rutten; H B Boom
Journal:  Biophys J       Date:  1993-05       Impact factor: 4.033

9.  Comparative analysis of modelled extracellular potentials.

Authors:  S M Fleisher
Journal:  Med Biol Eng Comput       Date:  1984-09       Impact factor: 2.602

10.  Determining surface potentials from current dipoles, with application to electrocardiography.

Authors:  R C Barr; T C Pilkington; J P Boineau; M S Spach
Journal:  IEEE Trans Biomed Eng       Date:  1966-04       Impact factor: 4.538

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  2 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.  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

  2 in total

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