Predicting individual variability in thermal sensation, PMV predictions, and local skin temperature differences using infrared thermography

Abstract

Thermal comfort is a perception of thermal environment by individuals. To assess thermal sensation predicted mean vote (PMV) and predicted percentage of dissatisfaction (PPD) are widely used. These relies on environmental parameters and subjective aspects like metabolic rate (M), and clothing insulation (I_cl). Additionally, skin temperature (t_sk) is another important indicator of comfort. However, measuring M, I_cl, and t_sk in real time is challenging. To address this issue, this research introduced a novel method using infrared thermography (IRT) to predict I_cl, t_sk, and PMV with M calculated based on individual variances. Experiments conducted in office environments during summer and winter and outcomes were analyzed by gender differences and body mass index (BMI) variation.

From the experimental outcomes, females reported significantly colder thermal sensation vote (TSV), higher I_cl, and lower M compared to males (p < 0.01). There were no significant gender differences in PMV predictions, however females PPD was higher in winter (p < 0.01). Females nose temperature was significantly lower (p < 0.01) and showed significant correlation with TSV (p < 0.01). Regarding BMI differences, BMI < 22 group had higher cold sensation and lower M compared to BMI > 22 group (p < 0.01). There were no significant morphological differences in PMV and PPD. BMI < 22 had significantly lower nose, cheek, fingertip temperature (p < 0.05) and these skin temperatures had significant correlation (p < 0.01) with TSV.

These results demonstrate the importance of individual difference in comfort prediction and illustrate the effectiveness of using IRT.