Evidence map›Paper›PMID 42655361›Full record

ArticleSensors (Basel, Switzerland)2026

Muscle Fatigue Investigation Using sEMG Signals and a DAQ Card Data Acquisition System in LabVIEW.

Zbigniew Krawiecki, Piotr Kuwałek

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Zbigniew KrawieckiInstitute of Electrical Engineering and Electronics, Poznan University of Technology, 61-138 Poznan, Poland.ORCID 0000-0001-5088-6768
Piotr KuwałekInstitute of Electrical Engineering and Electronics, Poznan University of Technology, 61-138 Poznan, Poland.ORCID 0000-0002-8746-7767

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study is to implement a custom-designed data acquisition system with a DAQ card, based on the virtual instrument concept in the LabVIEW environment, to investigate and analyze muscle fatigue using surface electromyography (sEMG) signals. The experiment was conducted as a pilot case study on a healthy volunteer, where sEMG signals from the biceps brachii muscle were collected during cyclic weighted exercises. Signal registration was performed across three distinct states: no fatigue, moderate fatigue, and high fatigue. The developed measurement system enabled signal acquisition, filtering, and analysis through both online processing and post-processing. Time-domain parameters (ARV, RMS, Umax) and frequency-domain parameters (ΣPS, MNF, MDF) were determined from three series of measurements. An analysis of parameter changes was conducted both within and between the series. The results indicated that with the onset of muscle fatigue, the participant exhibited a decrease in amplitude parameters and a shift in the power spectrum toward lower frequencies. Frequency-domain parameters, particularly MNF, exhibited higher diagnostic sensitivity than amplitude parameters. The obtained results confirm the technical feasibility of the developed virtual instrument for sEMG signal analysis. Furthermore, they suggest its potential utility for objective muscle condition assessment, establishing an engineering baseline for future research.

Indexed as

ElectromyographyMuscle FatigueSignal Processing, Computer-AssistedAdultHumansMaleMuscle, SkeletalSoftwarebiosignaldata acquisition (DAQ)frequency-domain analysisLabVIEWmuscle fatiguesurface electromyography (sEMG)time-domain parametersvirtual instrumentation

Identifiers

PMID42655361
PMCPMC13517491

What OpenQuestion holds

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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.