Real-time Non-invasive Heat Strain Prediction Model

Core temperature (Tc) is an excellent indicator of heat strain status. A computer model, Initial Capability Decision Aid (ICDA), was developed from existing models and algorithms to predict Tc and other physiological parameters in real-time from non-invasively measured inputs of heart rate (HR) and environment parameters together with the person's clothing and anthropometrics. The model was validated with laboratory studies. Tc prediction errors were small (0.11∼0.31ºC). Predictions of sweat rate and physiological strain index also agreed well (p>0.05) with measured values.