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Validity of the estimated core temperature algorithm during real-world prolonged walking exercise under warm ambient
Mandy A G Peggen1, Coen C W G Bongers2, Johannus Q de Korte3
1Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, the Netherlands.
Journal of Thermal Biology
|October 9, 2024
Summary
The Estimated Core Temperature (ECTemp™) algorithm showed acceptable group-level accuracy for estimating core body temperature during prolonged walking in heat. However, individual accuracy varied significantly, with only 17% of participants meeting the criteria for reliable estimation.
Area of Science:
- Exercise Physiology
- Biomedical Engineering
- Wearable Technology
Background:
- Non-invasive core body temperature (TC) estimation methods are emerging.
- The validity of the Estimated Core Temperature (ECTemp™) algorithm using heart rate (HR) during prolonged walking in warm conditions requires examination.
Purpose of the Study:
- To assess the group-level and individual participant-level accuracy of the ECTemp™ algorithm for estimating TC.
- To evaluate the algorithm's performance during real-world, prolonged walking exercise in warm ambient conditions.
Main Methods:
- Participants (n=18) walked distances of 30-50 km, with TC measured via ingestible capsules and HR recorded continuously.
- The ECTemp™ algorithm computed estimated core temperature (TC-est) from HR data.
- Bland-Altman analyses assessed agreement between TC and TC-est, with <0.1°C bias considered acceptable.
Main Results:
- Group-level analysis revealed a systematic bias of 0.09°C (limits of agreement ±0.44°C) between TC and TC-est.
- A weak correlation (r=0.28) was observed between measured and estimated core temperatures.
- Significant inter-individual variability in bias (-0.45°C to 0.62°C) was found, with only 3 participants (17%) achieving acceptable bias.
Conclusions:
- The ECTemp™ algorithm demonstrated acceptable group-level bias for estimating core body temperature during prolonged walking in warm weather.
- Individual accuracy was highly variable, limiting the algorithm's reliability for personal use in real-world exercise scenarios.
- Further improvements to the ECTemp™ algorithm are necessary to enhance individual user accuracy and reliability.
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