Core body temperature estimation model with thermal contact resistance compensation

Abstract

Continuous and accurate monitoring of core body temperature (CBT) is crucial for personal healthcare, clinical disease diagnosis, and enhancing athletic performance. Current CBT measurement methods typically ignore contact interface variation at the sensor-body interface, resulting in insufficient CBT measurement accuracy under daily wearable scenarios with varying sensor contact pressure. This study proposed a core temperature estimation model with thermal contact resistance (TCR) compensation, introducing the TCR factor into the computational equation to improve estimation accuracy in daily wearable scenarios. A numerical simulation of the temperature field between the human forehead and sensor was developed for model performance evaluation. Given the inconvenience of TCR measurement, this study proposed a method based on pressure/optical photoplethysmography (PPG) signals for updating thermal contact resistance. The mean absolute error of CBTER model under varying thermal contact resistance conditions was 0.26 °C, which was 27 % compared to traditional model errors in simulation. Using pressure updating methods, the result of human trials was 0.01±0.23 °C (with 95 % limits of agreement). Overall, the proposed method effectively compensated for errors in core body temperature estimation due to thermal contact resistance, holding potential for continuous core body temperature monitoring to meet healthcare needs scenarios.