Towards Climate-Resilient Buildings: A Statistical Analysis to Identify Crucial Comfort Measurement Parameters for Occupant Well-Being

This paper investigates the critical environmental and physiological parameters required to objectively measure indoor Global Sensation Vote (GSV) for climate-resilient, humancentric buildings. Within the MULTICLIMACT project framework (GA n. 101123538), an integrated measurement campaign monitored 8 office occupants using a tri-modal data acquisition strategy: environmental IoT sensors, wearable physiological devices, and regular subjective perception surveys. Statistical analysis of the measured data revealed that GSV is strongly associated with air quality, identifying CO2 and volatile organic compound (VOC) concentrations as the core environmental metrics to track CO2, mean (ρ=-0.704, p<0.001) and VOCmean (ρ=-0.673, p<0.001). Furthermore, the continuous measurements of air temperature and relative humidity are crucial for capturing latent thermal stress, while quantified ambient illuminance acts as a positive mitigator of comfort decay. Physiologically, GSV shifts were reliably quantified by autonomic stress markers; general discomfort correlated with sympathetic dominance (elevated LF/HF ratio and LFnu) and reduced parasympathetic activity (H Fnu and pNN50). By pinpointing these precise, measurable variables, this study provides the data-driven foundation needed to operationalize Personalized Comfort Models (PCMs), enabling dynamic building adjustments for personalized multidomain occupant well-being.