Exploring acclimation time in test-room environments via physiological indicators: Evolving human-centric personalized comfort measurement procedures

• Published in: Building and environment Vol. 277; p. 112924
• Main Authors: Gnecco, Veronica Martins, Chiucchiù, Agnese, Mansi, Silvia Angela, Pigliautile, Ilaria, Cosoli, Gloria, Arnesano, Marco, Pisello, Anna Laura
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2025
• Subjects: Acclimation time; Energy efficiency in buildings; Multi-domain comfort; Personalized comfort; Physiological human centric data; Test-room comfort; LL; EDA; PPD; Energy efficiency in buildings; PPG; HR; Physiological human centric data; IoT; SD; ML; ST; Personalized comfort; EEG; Multi-domain comfort; Test-room comfort; ECG; RMSSD; IEQ; Acclimation time; PMV; GNB; LF; PCM; LF/HF; SCL; HF
• ISSN: 0360-1323
• DOI: 10.1016/j.buildenv.2025.112924

•Acclimatation time is studied via environmental and personalized physiological data.•Physiological and environmental data are collected in three experiments in a test room.•Study identifies optimal acclimatation time for diverse tests carried out in test rooms.•25 min satisfy for 75 % acclimatation across all the participants.•Analysis of physiological data aid in stabilizing conditions for accurate comfort data. Comfort research in indoor environments often adopts climate chamber to ensure precision control and measurements’ accuracy while tracking human preferences. A critical step to guarantee that subjects’ answers reflect actual exposure conditions, unaffected prior experiences, is to dedicate an “acclimation time”. However, there is still debate within the scientific community regarding its optimum duration and calculation methods. This study proposes a novel approach to define acclimation time for comfort tests based on the analysis of physiological signals. Physiological and environmental signals from three different experimental campaigns, conducted in the Next.Room, were gathered in different thermal conditions to establish via data analysis procedures when subjects start stabilizing signals for Heart Rate (HR), Skin Temperature (ST) and tonic Electrodermal Activity (EDAt). Subjects were exposed to conditions from 20–30 °C, with durations of 60–110 min. Linear interpolations of data subgroups determined acclimation time as the point when the angular coefficient's standard deviation was below the group average for at least 3 min. A 25 min general threshold was defined to assure the acclimation of at least 75 % of the subjects, balancing differences between people and the prevention of subjects’ fatigue/boredom. A 40-minute-long acclimation period can be used when aiming at more accuracy in non-ideal conditions (close to or far from outdoor conditions). Real-time personalized acclimation methods could enhance experimental designs but may extend durations impractically. Physiological signals play an important role in defining the stability of each subjects’ conditions in different environmental setups, supporting a reliable experimental design process.