Optimal local skin temperatures for mean skin temperature estimation and thermal comfort prediction of seated person in thermally stratified environments.

Thermally stratified environments are universal in "real world" buildings. However, the studies on the machine learning model and mean skin temperature (MST), which was based on the analysis of Local Skin Temperatures (LSTs), were insufficient in thermally stratified environments. To create thermally stratified environments in this study, the air temperatures at the lower body parts in a climatic box were controlled independently from the upper body parts exposed in climate chamber, with 12 air temperature combinations of 22, 25, 28, and 31°C. Sixteen human subjects were recruited to collect thermal perceptions and measure their LSTs. The variations of LSTs and the optimal LSTs to estimate MST and predict thermal state were analyzed. Based on the classifications of LSTs and area of local skin, a new method using chest (0.42), forearm (0.21), thigh (0.30), and foot (0.07) was proposed to estimate MST. Its errors decreased by at least 22.8% as compared to the existing methods. Then, the model based on Random Forest was used to filter the optimal LSTs for the predictions of Thermal Sensation Vote (TSV) and Local Thermal Comfort (LTC). Results showed at least three LSTs were needed to reach a robust model prediction accuracy and generalization ability. The optimal LSTs for the predictions of TSV and LTC were (Forearm, upper arm, foot) and (Forearm, chest, thigh), respectively. This study contributes to provide the basic information of optimal LSTs to improve the accuracies of the thermal comfort predictions and MST estimation in the thermally stratified environments.

Using Upper Extremity Skin Temperatures to Assess Thermal Comfort in Office Buildings in Changsha, China.

Existing thermal comfort field studies are mainly focused on the relationship between the indoor physical environment and the thermal comfort. In numerous chamber experiments, physiological parameters were adopted to assess thermal comfort, but the experiments' conclusions may not represent a realistic thermal environment due to the highly controlled thermal environment and few occupants. This paper focuses on determining the relationships between upper extremity skin temperatures (i.e., finger, wrist, hand and forearm) and the indoor thermal comfort. Also, the applicability of predicting thermal comfort by using upper extremity skin temperatures was explored. Field studies were performed in office buildings equipped with split air-conditioning (SAC) located in the hot summer and cold winter (HSCW) climate zone of China during the summer of 2016. Psychological responses of occupants were recorded and physical and physiological factors were measured simultaneously. Standard effective temperature (SET*) was used to incorporate the effect of humidity and air velocity on thermal comfort. The results indicate that upper extremity skin temperatures are good indicators for predicting thermal sensation, and could be used to assess the thermal comfort in terms of physiological mechanism. In addition, the neutral temperature was 24.7 °C and the upper limit for 80% acceptability was 28.2 °C in SET*.