Statistical Simulation of Psychological Perception of Clothing Sensory Comfort

Abstract

Comfort is one of the most important attributes of clothing demanded by modern consumers. The objective of this paper is to simulate psychological sensory perceptions of clothing comfort by using ten sensations (clammy, clingy, sticky, damp, heavy, prickly, scratchy, fit, breathable and thermal). Twenty-two professional athletes were asked to participate in a series of trials wearing four different garments, cycling in a controlled climatic chamber. Subjective ratings on these sensory perceptions were recorded before, during and after their 90-minute cycling session. By using factor analysis with Quartimax rotation, 3- and 5-Factors models were generated. In the 5-Factors model, the sensations clammy, clingy, damp and sticky, formed the first factor, which related to moisture comfort and contributed around 41% of total variance of overall comfort. Prickly and scratchy formed the second factor, which related to tactile comfort and contributed about 20% of overall comfort variance. The remaining sensations, fit, breathable and thermal, were classified as three individual factors, each contributing around 10% of the total comfort variance. In the 3-Factors model, the sensation breathable was grouped into moisture comfort, while the sensations thermal and fit formed another factor, thermal-fit comfort. The 3- and 5-Factors models explained around 74% and 90% of the overall variance, respectively. A linear predictable model to overall comfort was developed using 3- and 5-Factors models and the relative contributions of individual factors as weights. The comfort score predicted from the models was compared with the actual comfort score rated by the subjects. The relationship between the simulation result and the actual comfort score was in good agreement, with r = 0.893 at p < 0.001 level.