Human comfort perception has a key role in building energy performance since it drives occupants’ behavior affecting energy consumptions. Standards consider only physical environmental parameters to assess human comfort in indoors neglecting the psychophysical conditions of individuals. This work proposes an innovative methodology simultaneously considering physical environmental parameters, physiological metrics, and psychological aspects. The novel experimentally based approach aims at producing a multipurpose comfort perception scheme, i.e. taking into account thermal, visual, acoustic, and air quality comfort. The initial findings of the campaign, focused on thermal comfort evaluation, are here presented. The tests are conducted in a continuously monitored, thermally controlled environment where each subject is exposed to different thermal stimuli while physiological signals, i.e. electroencephalogram (EEG), electro-dermal activity (EDA) and electrocardiogram (ECG), are measured with wearable devices, and his subjective response is investigated through surveys. The same experimental procedure is repeated in winter 2017 and summer 2018. The presented preliminary phase of data analysis aims to validate the proposed novel monitoring setup. In particular, ECG signal is analyzed, and significant features are extracted, i.e. Heart Rate Variability and Low on High Frequency ratio. The outlined temperature correlations are consistent with literature. Moreover, relations with other environmental parameters, i.e. CO2 concentration, are shown highlighting the potential of the presented setup of comfort investigation which allows a comprehensive monitoring. Future developments include data analysis through machine learning techniques to capture the most significative relations among collected environmental, physiological, and psychological parameters. These relations will be the experimental basis for the development of a novel occupants’ comfort prediction model, a useful tool for the improvement of buildings’ energy performance during both the earlier design stage and its operative life.
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