Human thermal sensation algorithm modelization via physiological thermoregulatory responses based on dynamic thermal...

Area of Science:

• Human-computer interaction
• Environmental science
• Biomedical engineering

Background:

• Cabin thermal conditions fluctuate, stressing occupants' self-thermoregulation.
• Effective thermal management requires real-time individual thermal sensation recognition.
• Existing models are for simulations, not practical field surveys.

Purpose of the Study:

• To construct a human thermal sensation model for real-world vehicle environments.
• To evaluate human thermal sensation using physiological responses.
• To enable auto-adjustable thermal environment management.

Main Methods:

• Developed a thermal sensation model using exponential functions relating sensation to pulse rate and blood pressure.
• Collected subjective thermal sensation scores via a seven-point scale questionnaire.
• Measured physiological responses (blood pressure, pulse rate, SpO2) using wearable sensors.

Main Results:

• Pulse rate positively correlated, blood pressure negatively correlated with warmer temperatures.
• Parameter change rate effectively tracked thermal sensation trends, avoiding raw data inconsistencies.
• A 10% difference in PR and MAP change rate observed between cold and hot thermal sensations.

Conclusions:

• The thermal sensation model, fitted with physiological data and subjective votes, achieved R² > 0.8.
• The model is suitable for evaluating human thermal sensation in practical settings.
• Physiological responses from smart wearables can effectively indicate thermal state for environmental control.