Evidence map›Paper›PMID 41650002›Full record

ArticlePloS one2026

Research on the influence of virtual reality on muscle fatigue during rowing ergometer exercise - pilot study.

Natalia Daniel, Jerzy Małachowski, Kamil Sybilski, Dariusz Siemiaszko, Kamil Klicki

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Natalia DanielMilitary University of Technology, Faculty of Mechatronics, Armament and Aviation, Institute of Rocket Technology and Mechatronics, Warsaw, Poland.ORCID https://orcid.org/0000-0002-8289-4428
Jerzy MałachowskiMilitary University of Technology, Faculty of Mechanical Engineering, Institute of Mechanics & Computational Engineering, Warsaw, Poland.ORCID https://orcid.org/0000-0003-1300-8020
Kamil SybilskiMilitary University of Technology, Faculty of Mechanical Engineering, Institute of Mechanics & Computational Engineering, Warsaw, Poland.
Dariusz SiemiaszkoMilitary University of Technology, Faculty of Chemistry and New Technology, Department of Functional Materials and Hydrogen Technology, Warsaw, Poland.
Kamil KlickiMilitary University of Technology, Faculty of Mechatronics, Armament and Aviation, Institute of Rocket Technology and Mechatronics, Warsaw, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing popularity of virtual reality (VR) applications has been reflected in numerous studies, particularly those examining the effects of VR on the human body, physical activity, and sports training. Comparative research suggests that simulated environments can influence physiological and psychological responses in distinct ways. The integration of VR with electromyographic (EMG) systems opens new opportunities to study biofeedback and muscle activation during exercise in real-time. However, only a limited number of studies have provided quantitative data on muscle fatigue. In the present research eight healthy male participants from previously described studies were examined using a VR environment to explore muscle fatigue. EMG signals were recorded from three muscle groups, and knee flexion angles were monitored. A VR simulation developed in Unreal Engine 5 was designed to reproduce a natural river scene for rowing training. The Discrete Wavelet Transform (DWT) was applied to both previously collected and VR-based data, calculating median frequency (MDF) distributions and linear regression for lower extremity muscles. Wilcoxon signed-rank tests comparing VR and non-VR conditions for the measured muscles: the Rectus Femoris, Biceps Femoris, and Gastrocnemius Lateralis, did not reveal statistically significant differences (all p > 0.05). Although no significant differences were observed, the proposed methodology introduces a valuable framework for quantitative fatigue assessment. By integrating VR with EMG analysis, this approach provides new perspectives for investigating muscle fatigue and its modulation in immersive environments.

Indexed as

ExerciseMuscle FatigueVirtual RealityWater SportsAdultElectromyographyErgometryHumansMaleMuscle, SkeletalPilot ProjectsYoung Adult

Identifiers

PMID41650002
PMCPMC12880715

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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.