Evidence map›Paper›PMID 25844148›Full record

ArticleInterface focus2015

Predicting electromyographic signals under realistic conditions using a multiscale chemo-electro-mechanical finite element model.

Mylena Mordhorst, Thomas Heidlauf, Oliver Röhrle

Abstract read
In one paragraph

Article in Interface focus, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mylena MordhorstInstitute of Applied Mechanics (CE) , University of Stuttgart , Pfaffenwaldring 7, 70569 Stuttgart , Germany ; Stuttgart Research Centre for Simulation Technology , Pfaffenwaldring 5a, 70569 Stuttgart , Germany.
Thomas HeidlaufInstitute of Applied Mechanics (CE) , University of Stuttgart , Pfaffenwaldring 7, 70569 Stuttgart , Germany ; Stuttgart Research Centre for Simulation Technology , Pfaffenwaldring 5a, 70569 Stuttgart , Germany.ORCID 0000-0001-9381-1598
Oliver RöhrleInstitute of Applied Mechanics (CE) , University of Stuttgart , Pfaffenwaldring 7, 70569 Stuttgart , Germany ; Stuttgart Research Centre for Simulation Technology , Pfaffenwaldring 5a, 70569 Stuttgart , Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents a novel multiscale finite element-based framework for modelling electromyographic (EMG) signals. The framework combines (i) a biophysical description of the excitation-contraction coupling at the half-sarcomere level, (ii) a model of the action potential (AP) propagation along muscle fibres, (iii) a continuum-mechanical formulation of force generation and deformation of the muscle, and (iv) a model for predicting the intramuscular and surface EMG. Owing to the biophysical description of the half-sarcomere, the model inherently accounts for physiological properties of skeletal muscle. To demonstrate this, the influence of membrane fatigue on the EMG signal during sustained contractions is investigated. During a stimulation period of 500 ms at 100 Hz, the predicted EMG amplitude decreases by 40% and the AP propagation velocity decreases by 15%. Further, the model can take into account contraction-induced deformations of the muscle. This is demonstrated by simulating fixed-length contractions of an idealized geometry and a model of the human tibialis anterior muscle (TA). The model of the TA furthermore demonstrates that the proposed finite element model is capable of simulating realistic geometries, complex fibre architectures, and can include different types of heterogeneities. In addition, the TA model accounts for a distributed innervation zone, different fibre types and appeals to motor unit discharge times that are based on a biophysical description of the α motor neurons.

Indexed as

bidomainbiophysical modellingelectromyographyfatiguefinite element methodskeletal muscle

Identifiers

PMID25844148
PMCPMC4342944

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.