Evidence map›Paper›PMID 31067754›Full record

Trial reportSensors (Basel, Switzerland)2019

The Piezo-resistive MC Sensor is a Fast and Accurate Sensor for the Measurement of Mechanical Muscle Activity.

Andrej Meglič, Mojca Uršič, Aleš Škorjanc, Srđan Đorđević, Gregor Belušič

Open access · goldAbstract readClinical Trial
In one paragraph

Trial report in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 35% 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.

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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

5 authors at 2 institutions in 1 country.

Andrej MegličDepartment of Biology, Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia. andrej.meglic@bf.uni-lj.si.
Mojca UršičDepartment of Biology, Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia. mojca.ursic@danceart.si.
Aleš ŠkorjancDepartment of Biology, Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia. ales.skorjanc@bf.uni-lj.si.
Srđan ĐorđevićTMG-BMC Ltd., Štihova ulica 24, 1000 Ljubljana, Slovenia. srdjand@tmg.si.
Gregor BelušičDepartment of Biology, Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia. gregor.belusic@bf.uni-lj.si.ORCID 0000-0003-3571-1948
University of Ljubljana · SITMG-BMC (Slovenia) · SI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A piezo-resistive muscle contraction (MC) sensor was used to assess the contractile properties of seven human skeletal muscles (vastus medialis, rectus femoris, vastus lateralis, gastrocnemius medialis, biceps femoris, erector spinae) during electrically stimulated isometric contraction. The sensor was affixed to the skin directly above the muscle centre. The length of the adjustable sensor tip (3, 4.5 and 6 mm) determined the depth of the tip in the tissue and thus the initial pressure on the skin, fatty and muscle tissue. The depth of the tip increased the signal amplitude and slightly sped up the time course of the signal by shortening the delay time. The MC sensor readings were compared to tensiomyographic (TMG) measurements. The signals obtained by MC only partially matched the TMG measurements, largely due to the faster response time of the MC sensor.

Indexed as

Electric ImpedanceAdolescentBiomechanical PhenomenaElectric StimulationElectromyographyFemaleHumansMuscle ContractionMuscle, SkeletalTime FactorsYoung Adultelectrically stimulated skeletal muscle contractionmuscle contraction sensortensiomyography

Identifiers

PMID31067754
PMCPMC6539344
OpenAlexW2944277309

What OpenQuestion holds

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LicenceCC BY
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.