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Using Near-Infrared Spectroscopy Wearable Devices to Identify Central Versus Peripheral Limitations During Exercise

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Dynamic correlation between chest temperature entropy and physiological load indicators, and excess post-exercise

Songzi Cui^1,2, Ning Du^1,2, Zhongqian Liu²

¹Department of Orthopaedics, Fourth Medical Centre of Chinese PLA General Hospital, Beijing, China.

Frontiers in Physiology

|September 26, 2025

Summary

Chest temperature entropy, measured by infrared thermography, accurately reflects exercise intensity and metabolic changes. This novel marker shows potential for non-invasively monitoring exercise load and recovery.

Keywords:

blood lactate response entropy analysis incremental exercise protocol oxygen consumption thermal imaging

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Area of Science:

Exercise Physiology
Biomedical Engineering
Thermography Applications

Background:

Understanding physiological responses to exercise is crucial for training optimization and health.
Non-invasive methods for monitoring exercise intensity and recovery are highly sought after.
Infrared thermography (IRT) offers a potential tool for assessing physiological changes during physical exertion.

Purpose of the Study:

To investigate the dynamic relationship between chest temperature entropy and physiological load indicators during incremental cycling.
To explore the association between chest temperature entropy and excess post-exercise oxygen consumption (EPOC).
To evaluate the potential of chest temperature entropy as a non-invasive marker for exercise load and recovery.

Main Methods:

Utilized high-sampling-rate infrared thermography (IRT) to measure chest temperature distribution.
Participants performed incremental cycling tests until exhaustion.
Simultaneously measured oxygen consumption (VO₂), blood lactate, external load, and calculated temperature entropy.

Main Results:

Significant positive correlations were observed between entropy increase and VO₂, blood lactate, and external load (R² > 0.7).
Individual analyses confirmed strong associations between entropy and these physiological markers (r > 0.69).
Chest temperature entropy showed a significant association with EPOC during recovery, despite inter-individual variability.

Conclusions:

Chest temperature entropy dynamically reflects exercise-induced metabolic changes.
This entropy measure partially explains post-exercise recovery processes.
Chest temperature entropy shows promise as a novel, non-invasive marker for monitoring exercise load and recovery.