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

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

PMC · DOI: 10.3390/mps9010015 · Methods and Protocols · 2026-01-21

## TL;DR

This paper introduces a standardized method using wearable sensors to monitor exercise in isolated and extreme environments, enabling reliable physiological data collection.

## Contribution

A reproducible multimodal protocol for exercise monitoring in confined environments using sEMG, IMU, and ECG.

## Key findings

- The protocol enabled stable real-time data acquisition and reliable repetition-level segmentation.
- sEMG mean frequency showed sensitivity to differences in movement strategy.
- Cardiac measures showed limited condition-specific modulation.

## 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.

## Full-text entities

- **Genes:** SEMG1 (semenogelin 1) [NCBI Gene 6406] {aka CT103, SEMG, SGI, dJ172H20.2}
- **Diseases:** losses of muscle and bone mass (MESH:D001847), injury (MESH:D014947), ICE (MESH:C565377), fatigue (MESH:D005221)
- **Chemicals:** ICE (-), carbon dioxide (MESH:D002245), oxygen (MESH:D010100), Po (MESH:D011059), Li (MESH:D008094)
- **Species:** Homo sapiens (human, species) [taxon 9606]
- **Mutations:** start/stop

## Full text

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## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12922138/full.md

## References

41 references — full list in the complete paper: https://tomesphere.com/paper/PMC12922138/full.md

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Source: https://tomesphere.com/paper/PMC12922138