A personalized thermal environment is an effective way to ensure a good thermal sensation for individuals. Since local thermal sensation and temperature distribution are affected by individual physiological differences, it is necessary to study the effects of physiological parameters. The purpose of this study was to investigate the effects of internal structures and tissue composition on head temperature distribution and thermal sensation. A new mathematical model based on fuzzy logic control was established, the internal structure and tissue composition of the head were obtained by magnetic resonance imaging (MRI), and the local thermal sensation (LTS) index was used to evaluate the thermal sensation. Based on the mathematical model and the real physiological data, the head temperature and local sensation changes under different parameters were investigated, and the sensitivity of thermal sensation relative to the differences in tissue thickness was analyzed. The results show that skin tissue had the highest influence (
) on head temperature, followed by muscle tissue (
), and the influence of adipose tissue (
) was the lowest. LTS was most sensitive to skin thickness variation, with an average sensitivity coefficient of 1.58, while the muscle tissue had an average sensitivity coefficient of 0.2, and the sensitivity coefficient of fat was relatively small, at a value of 0.04.
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