Evidence map›Paper›PMID 33192993›Full record

ReviewFrontiers in neurology2020

Critical Appraisal of Surface Electromyography (sEMG) as a Taught Subject and Clinical Tool in Medicine and Kinesiology.

Vladimir Medved, Sara Medved, Ida Kovač

Registry-linked trialOpen access · goldAbstract readReview
In one paragraph

Review in Frontiers in neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04706169 (Age-related Differences in Motor Recruitment Patterns of the Shoulder in Dynamic and Isometric Contractions. A Cross-sectional Study), which is not on this map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 21% of its field
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.

NCT04706169 completednot on this map

Age-related Differences in Motor Recruitment Patterns of the Shoulder in Dynamic and Isometric Contractions. A Cross-sectional Study

Typeobservational_patient_registrySponsorUniversity of Castilla-La ManchaRan2015 to 2019Enrolled60ConditionsElectromyographyArmsSurface Electromyography
3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Advances in 2D materials for wearable biomonitoring.Materials science & engineering. R, Reports : a review journal · 2025
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  19. Multi-user motion recognition using sEMGFrontiers in neurorobotics · 2022
    Article
  20. Article
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 at 2 institutions in 1 country.

Vladimir MedvedFaculty of Kinesiology, University of Zagreb, Zagreb, Croatia.
Sara MedvedClinic of Psychiatry and Psychological Medicine, University Hospital Center Zagreb, Zagreb, Croatia.
Ida KovačPolyclinic Medical Body Balance, Zagreb, Croatia.
University Hospital Centre Zagreb · HRUniversity of Zagreb · HR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The characteristics and state of knowledge of bioelectric signals such as ECG, EEG, and EMG are initially discussed. This serves as the basis for exploration of the degree of scholastic coverage and understanding of the level of clinical acceptance of respective bioelectric signal subtypes during the last 60 or so years. The review further proceeds to discuss surface EMG (sEMG). The status of the field in terms of teaching and academic training related to sEMG is examined, and its clinical acceptance in several areas of medicine and kinesiology, including neurology, psychology, psychiatry, physiatry, physical medicine and rehabilitation, biomechanics and motor control, and gnathology, is evaluated. A realistic overview of the clinical utility of the measurement of sEMG signals and their interpretation and usage, as well as of perspectives on its development, are then provided. The main focus is on the state of the field in Croatia. EMG signals are viewed as "windows" into the function of the neuro-muscular system, a complex and hierarchically organized system that controls human body posture and gross body movement. New technical and technological means to enable the detection and measurement of these signals will contribute to increased clinical acceptance, provided current scientific, educational, and financial obstacles can be removed.

Indexed as

bioelectric signalsclinical medicinekinesiologyphysiotherapyrehabilitationsurface electromyographyteaching

Identifiers

PMID33192993
PMCPMC7649227
OpenAlexW3095538211

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.