ArticleScientific reports2022
Preliminary study of thermal density distribution and entropy analysis during cycling exercise stress test using infrared thermography.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- Deep learning-based infrared thermography reveals reproducible uniform and individual thermoregulatory responses during running.Scientific reports · 2026Article
- Detection of activated perforasome patterns and the correlation with acute internal load parameters during and following incremental cycling.European journal of applied physiology · 2026Article
- The Challenge of Measuring Exercise: Advancing Metrological Barriers in Wearable Sensing.JMIR mHealth and uHealth · 2025Review
- Thermography in Bike Fitting: A Literature Review.Sensors (Basel, Switzerland) · 2025Review
- Can Infrared Thermal Imaging Reflect Exercise Load? An Incremental Cycling Exercise Study.Bioengineering (Basel, Switzerland) · 2025Article
- Dynamic correlation between chest temperature entropy and physiological load indicators, and excess post-exercise oxygen consumption during incremental cycling exercise.Frontiers in physiology · 2025Article
- Thermographic Changes following Short-Term High-Intensity Anaerobic Exercise.Life (Basel, Switzerland) · 2023Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Considerable differences related to the results of temperature changes acquired during exercise exist, and in many cases, these lead to poor correlation with physiological variables. In this preliminary study we investigated the temperature changes and the temperature distribution (entropy) of the torso during a graded cycling exercise stress test using thermal imaging and studied the correlation between the increase in pulmonary ventilation (VE) and the changes in the surface temperature of the anterior torso during exercise. Thermal images of the anterior torso were captured every 30 s during the exercise, while the resistance was gradually increased every minute until exhaustion. The thermal images were processed to obtain a mean temperature in the regions of interest (ROI) (chest, forehead, and abdomen). We also developed an algorithm to calculate the distribution of temperature and texture (entropy) within each ROI. No changes were found in absolute temperatures. However, the entropy of the chest surface area increased significantly throughout the exercise test, compared with baseline temperature at rest. This increase in entropy was significantly correlated with exercise duration and intensity (p < 0.001). Furthermore, a high correlation between the increase in VE and chest entropy during exercise was detected (r = 0.9515). No correlations were found between the increase in entropy and the abdomen or the forehead compared with the VE. The non-invasive IR thermal imaging during graded exercise, combined with advanced image processing, successfully correlates surface thermography with exercise duration and pulmonary ventilation.
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Registered trials
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 Socratic graph.