Estimation of human core temperature from sequential heart rate observations

Area of Science:

• Occupational health and safety
• Biomedical engineering
• Environmental physiology

Background:

• Core body temperature (CT) and heart rate (HR) are key indicators of heat stress.
• Continuous CT monitoring is challenging in real-world occupational settings.
• Accurate thermal strain assessment is crucial for preventing heat exhaustion.

Purpose of the Study:

• To develop and validate a model for estimating core body temperature (CT) using heart rate (HR) data.
• To provide a practical, non-invasive method for monitoring thermal work strain.
• To enhance heat exhaustion prevention strategies in occupational environments.

Main Methods:

• A Kalman filter model was developed to estimate CT from HR measurements.
• Model training utilized data from 17 volunteers during a 24-hour military field exercise.
• Validation involved laboratory and field studies (N=83) with diverse environmental and physiological conditions.

Main Results:

• The CT estimation model demonstrated a low bias of -0.03 ± 0.32 °C.
• 95% of CT estimates fell within ±0.63 °C of actual values.
• Model accuracy is comparable to invasive CT measurement methods.

Conclusions:

• The developed HR-based CT estimation model offers a practical solution for monitoring thermal strain.
• This approach can aid in the early detection of heat exhaustion in occupational settings.
• The model provides sufficient accuracy for workplace thermal risk assessment.