Effects of the indoor environment on EEG and thermal comfort assessment in males

Abstract

This study investigated the effect of indoor thermal conditions on electroencephalogram (EEG) signals and used logistic regression to discriminate indoor, thermal comfort. Twenty male subjects were recruited to record resting EEG signals under thermal conditions consisting of a combination of temperature, relative humidity, and air velocity. Subjective questionnaires were used to collect individuals' perceptions of the environment and as classification criteria for developing logistic regression models. The results indicated that at 22 °C and 25 °C, θ, β1, β2, and γ waves were highly similar, and velocity was also highly similar for all EEG waves at 0.5 and 1 m/s. For β1, β2, and γ, 70% RH can be used as the high humidity cut-off point in the humidity test. In addition, regression models for indoor comfort discrimination utilizing the frequency bands relevant to comfort are regressed, and the total model revealed that 88.6% of the data were correctly categorized. This research serves as a starting point for further research into the coupled environment and neuronal mechanisms.