Influence of gender, age and BMI on human physiological response and thermal sensation for transient indoor environments with displacement ventilation

Thermophysiological comfort models allow the prediction of subjective thermal sensation for transient and inhomogeneous boundary conditions for a defined validation range. However, their validation ranges are rela-ively limited due to only low availability of high quality experimental measurement data. The present work aims to provide a high-resolution and well-documented data set to develop and validate scalable modeling approaches. Therefore, a 300 min test study with a total of 48 subjects is conducted in the climate test bench Aachen Comfort Cube (ACCu). We varied the mean temperature from 18 degrees C to 28 degrees C and back to 18 degrees C. We use the experiments to analyze differences with regard to the physiological parameters of gender, age and body -mass-index (BMI). For this purpose, core body and skin temperatures at 25 positions are recorded and related to local and global subjective evaluations. The results show different statistical differences in skin temperature and thermal sensation depending on the subgroup parameters and boundary conditions. These findings are mostly in agreement with general findings of existing literature. However, a significant difference in local skin temperature does not consequently lead to differences for local thermal sensation. Additionally, for nearly equal local skin temperatures significant difference in local thermal sensation can be found. BMI respectively body fat percentage seems so be the most influencing parameter on physiological responses due to lower thermal conductivity of fat tissue layer. These results highlight the need for separate scaling of physiological and psychological submodels regarding individualization approaches. The available data allow such an approach.

Automated summary

This study provides a high-resolution dataset to develop and validate scalable modeling approaches for predicting thermal sensation. Results indicate that BMI and body fat percentage are significant influencing factors on physiological responses, emphasizing the need for individualized modeling.