Evidence map›Paper›PMID 25256114›Full record

ArticleSensors (Basel, Switzerland)2014

In-vivo measurement of muscle tension: dynamic properties of the MC sensor during isometric muscle contraction.

Srđan Đorđević, Sašo Tomažič, Marco Narici, Rado Pišot, Andrej Meglič

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

11 citing papers in PubMed, 31 citations in OpenAlex.

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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

5 authors at 4 institutions in 2 countries.

Srđan ĐorđevićTMG-BMC Ltd., Splitska 5, Ljubljana 1000, Slovenia. andrej.meglic.info@gmail.com.
Sašo TomažičFaculty of Electrical Engineering, University of Ljubljana, Tržaška 25, Ljubljana 1000, Slovenia. saso.tomazic@fe.uni-lj.si.
Marco NariciUniversity of Nottingham, School of Graduate Entry Medicine and Health, Derby Royal Hospital, Uttoxeter Road, Derby DE22 3DT, UK. marco.narici@nottingham.ac.uk.
Rado PišotInstitute for Kinesiology Research, Science and Research Centre of the University of Primorska, Garibaldijeva 1, Koper 6000, Slovenia. rado.pisot@zrs.upr.si.
Andrej MegličTMG-BMC Ltd., Splitska 5, Ljubljana 1000, Slovenia. andrej.meglic.info@gmail.com.
University of Primorska · SITMG-BMC (Slovenia) · SIUniversity of Ljubljana · SIUniversity of Nottingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skeletal muscle is the largest tissue structure in our body and plays an essential role for producing motion through integrated action with bones, tendons, ligaments and joints, for stabilizing body position, for generation of heat through cell respiration and for blood glucose disposal. A key function of skeletal muscle is force generation. Non-invasive and selective measurement of muscle contraction force in the field and in clinical settings has always been challenging. The aim of our work has been to develop a sensor that can overcome these difficulties and therefore enable measurement of muscle force during different contraction conditions. In this study, we tested the mechanical properties of a "Muscle Contraction" (MC) sensor during isometric muscle contraction in different length/tension conditions. The MC sensor is attached so that it indents the skin overlying a muscle group and detects varying degrees of tension during muscular contraction. We compared MC sensor readings over the biceps brachii (BB) muscle to dynamometric measurements of force of elbow flexion, together with recordings of surface EMG signal of BB during isometric contractions at 15° and 90° of elbow flexion. Statistical correlation between MC signal and force was very high at 15° (r = 0.976) and 90° (r = 0.966) across the complete time domain. Normalized SD or σN = σ/max(FMC) was used as a measure of linearity of MC signal and elbow flexion force in dynamic conditions. The average was 8.24% for an elbow angle of 90° and 10.01% for an elbow of angle 15°, which indicates high linearity and good dynamic properties of MC sensor signal when compared to elbow flexion force. The next step of testing MC sensor potential will be to measure tension of muscle-tendon complex in conditions when length and tension change simultaneously during human motion.

Indexed as

Biosensing TechniquesHumansIsometric ContractionMuscle ContractionMuscle Tonus

Identifiers

PMID25256114
PMCPMC4208254
OpenAlexW1964396776

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.