Evidence map›Paper›PMID 26886908›Full record

ArticlePloS one2016

A Finite Element Model Approach to Determine the Influence of Electrode Design and Muscle Architecture on Myoelectric Signal Properties.

A Teklemariam, E F Hodson-Tole, N D Reeves, N P Costen, G Cooper

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Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

A TeklemariamSchool of Engineering, Manchester Metropolitan University, Manchester, United Kingdom.
E F Hodson-ToleSchool of Healthcare Science, Manchester Metropolitan University, Manchester, United Kingdom.
N D ReevesSchool of Healthcare Science, Manchester Metropolitan University, Manchester, United Kingdom.
N P CostenSchool of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, Manchester, United Kingdom.
G CooperSchool of Mechanical, Aerospace & Civil Engineering, University of Manchester, Manchester, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSurface electromyography (sEMG) is the measurement of the electrical activity of the skeletal muscle tissue detected at the skin's surface. Typically, a bipolar electrode configuration is used. Most muscles have pennate and/or curved fibres, meaning it is not always feasible to align the bipolar electrodes along the fibres direction. Hence, there is a need to explore how different electrode designs can affect sEMG measurements.

methodA three layer finite element (skin, fat, muscle) muscle model was used to explore different electrode designs. The implemented model used as source signal an experimentally recorded intramuscular EMG taken from the biceps brachii muscle of one healthy male. A wavelet based intensity analysis of the simulated sEMG signal was performed to analyze the power of the signal in the time and frequency domain.

resultsThe model showed muscle tissue causing a bandwidth reduction (to 20-92- Hz). The inter-electrode distance (IED) and the electrode orientation relative to the fibres affected the total power but not the frequency filtering response. The effect of significant misalignment between the electrodes and the fibres (60°-90°) could be reduced by increasing the IED (25-30 mm), which attenuates signal cancellation. When modelling pennated fibres, the muscle tissue started to act as a low pass filter. The effect of different IED seems to be enhanced in the pennated model, while the filtering response is changed considerably only when the electrodes are close to the signal termination within the model. For pennation angle greater than 20°, more than 50% of the source signal was attenuated, which can be compensated by increasing the IED to 25 mm.

conclusionDifferences in tissue filtering properties, shown in our model, indicates that different electrode designs should be considered for muscle with different geometric properties (i.e. pennated muscles).

Indexed as

ElectromyographyFinite Element AnalysisModels, TheoreticalSignal Processing, Computer-AssistedElectricityElectrodesMuscle, SkeletalTime Factors

Identifiers

PMID26886908
PMCPMC4757537

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.