Evidence map›Paper›PMID 41718317›Full record

ArticleMethods and protocols2026

Multimodal Wearable Monitoring of Exercise in Isolated, Confined, and Extreme Environments: A Standardized Method.

Jan Hejda, Marek Sokol, Lydie Leová, Petr Volf, Jan Tonner, Wei-Chun Hsu, Yi-Jia Lin, Tommy Sugiarto, Miroslav Rozložník, Patrik Kutílek

Abstract read
In one paragraph

Article in Methods and protocols, 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. 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

10 authors.

Jan HejdaFaculty of Biomedical Engineering, Czech Technical University in Prague, 27201 Kladno, Czech Republic.ORCID 0000-0003-2461-6283
Marek SokolFaculty of Biomedical Engineering, Czech Technical University in Prague, 27201 Kladno, Czech Republic.ORCID 0000-0001-5795-7581
Lydie LeováFaculty of Biomedical Engineering, Czech Technical University in Prague, 27201 Kladno, Czech Republic.ORCID 0000-0002-3460-7914
Petr VolfFaculty of Biomedical Engineering, Czech Technical University in Prague, 27201 Kladno, Czech Republic.ORCID 0000-0001-7230-7421
Jan TonnerFaculty of Biomedical Engineering, Czech Technical University in Prague, 27201 Kladno, Czech Republic.
Wei-Chun HsuGraduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan.
Yi-Jia LinGraduate Institute of A.I. Cross-Disciplinary Technology, National Taiwan University of Science and Technology, Taipei 106, Taiwan.
Tommy SugiartoIndustrial Technology Research Institute, Hsinchu 310, Taiwan.ORCID 0000-0002-8814-1275
Miroslav RozložníkHydronaut Project a.s., 15500 Prague, Czech Republic.ORCID 0000-0002-0584-4523
Patrik KutílekFaculty of Biomedical Engineering, Czech Technical University in Prague, 27201 Kladno, Czech Republic.ORCID 0000-0003-4160-9851

Funding

Taiwan National Science and Technology Council NSTC-112-2923-H-011-001-MY3Technology Agency of the Czech Republic TM04000062
6 · The paper itself

Abstract

This study presents a standardized method for multimodal monitoring of exercise execution in isolated, confined, and extreme (ICE) environments, addressing the need for reproducible assessment of neuromuscular and cardiovascular responses under space- and equipment-limited conditions. The method integrates wearable surface electromyography (sEMG), inertial measurement units (IMU), and electrocardiography (ECG) to capture muscle activation, movement, and cardiac dynamics during space-efficient exercise. Ten exercises suitable for confined habitats were implemented during analog missions conducted in the DeepLabH03 facility, with feasibility evaluated in a seven-day campaign involving three adult participants. Signals were synchronized using video-verified repetition boundaries, sEMG was normalized to maximum voluntary contraction, and sEMG amplitude- and frequency-domain features were extracted alongside heart rate variability indices. The protocol enabled stable real-time data acquisition, reliable repetition-level segmentation, and consistent detection of muscle-specific activation patterns across exercises. While amplitude-based sEMG indices showed no uniform main effect of exercise, robust exercise-by-muscle interactions were observed, and sEMG mean frequency demonstrated sensitivity to differences in movement strategy. Cardiac measures showed limited condition-specific modulation, consistent with short exercise bouts and small sample size. As a proof-of-concept feasibility study, the proposed protocol provides a practical and reproducible framework for multimodal physiological monitoring of exercise in ICE analogs and other constrained environments, supporting future studies on exercise quality, training load, and adaptive feedback systems. The protocol is designed to support near-real-time monitoring and forms a technical basis for future exercise-quality feedback in confined habitats.

Indexed as

confined environmentselectromyographyexercise monitoringinertial measurement unitsmethodswearable sensors

Identifiers

PMID41718317
PMCPMC12922138

What OpenQuestion holds

Textmetadata
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.