A Machine Learning-Based Method for Thermal Parameter Estimation in MMW Exposure

Experiments using laboratory animals have shown thatmillimeter wave exposure affects thermoregulation, including skin blood flow.This study aims to improve the calculation of temperature elevation by analyzing the skin and muscle blood flow coefficients.Using principal component analysis (PCA), we analyzed the calculated temperature elevation at the skin surface of rat dorsal model, which follows an exponential curve converging to a steady state over time.Our findings suggest that PCA method enables the simplification and visualization of thermal effects evaluation and, to some extent, allows for the prediction of temperature elevation results due to MMW exposure when the muscle blood flow coefficient is changed.