Abstract
This paper presents a new approach, in applying the Pierce two-node model, to predict local skin temperatures of individual body parts with good accuracy. In this study, local skin temperature measurements at 24 sites on the bodies of 11 human subjects were carried out in a controlled environment under three different indoor conditions (i.e. neutral, warm and cold). The neutral condition measurements were used to adjust the local skin set-points in the model for each body part. Additional modifications to the calculation algorithm were introduced corresponding to different body parts. The local core set-points were then calculated, using a line search method, as the input values that allow the model to predict the skin temperatures with maximum deviation of ±0.1°C for the neutral condition. The model predictability was verified for the other two indoor conditions, and the results show that the modified model predicts local skin temperatures with average deviation of ±0.3°C.