Evidence map›Paper›PMID 23001682›Full record

ArticleEuropean journal of applied physiology2013

Uneven spatial distribution of surface EMG: what does it mean?

Alessio Gallina, Roberto Merletti, Marco Gazzoni

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Article in European journal of applied physiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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  16. Regional activation within the vastus medialis in stimulated and voluntary contractions.Journal of applied physiology (Bethesda, Md. : 1985) · 2016
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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.

Alessio GallinaLaboratory for Engineering of the Neuromuscular System, LISiN, Politecnico di Torino, Torino, Italy. alessio.gallina@delen.polito.it
Roberto Merletti
Marco Gazzoni

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this work is to show how changes in surface electromyographic activity (sEMG) during a repetitive, non-constant force contraction can be detected and interpreted on the basis of the amplitude distribution provided by high-density sEMG techniques. Twelve healthy male subjects performed isometric shoulder elevations, repeating five times a force ramp profile up to 25 % of the maximal voluntary contraction (MVC). A 64-electrode matrix was used to detect sEMG from the trapezius muscle. The sEMG amplitude distribution was obtained for the force levels in the range 5-25 % MVC with steps of 5 % MVC. The effect of force level, subject, electrode position and ramp repetition on the sEMG amplitude distribution was tested. The sEMG amplitude was significantly smaller in the columns of the electrode grid over the tendons (repeated measures ANOVA, p < 0.01). The barycentre of the distribution of sEMG amplitude was subject-specific (Kruskal-Wallis test, p < 0.01), and shifted caudally with the increase of force levels and cranially with the repetition of the motor task (both p < 0.01, repeated measures ANOVA). The results are discussed in terms of motor unit recruitment in different muscle sub-portions. It is concluded that the sEMG amplitude distribution obtained by multichannel techniques provides useful information in the study of muscle activity, and that changes in the spatial distribution of the recruited motor units during a force varying isometric contraction might partially explain the variability observed in the activation pattern of the upper trapezius muscle.

Indexed as

ElectromyographyIsometric ContractionAction PotentialsAdultAnalysis of VarianceHumansMaleMotor ActivityMuscle, SkeletalPredictive Value of TestsShoulderSignal Processing, Computer-AssistedTime FactorsYoung Adult

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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.