Understanding how environmental conditions influence human resilience is critical for designing climate-responsive buildings. Sleep quality represents a key human-centric indicator of environmental resilience, impacting cumulative exposure to different stimuli. This study presents an exploratory analysis of longitudinal monitoring data which examines how environmental exposures, physiological responses, and personal characteristics interact to shape human resilience through sleep quality in real-life settings. Sixteen participants were continuously monitored for ten days using wearable devices to collect physiological data and characterize environmental exposure patterns associated with sleep quality. A composite Predicted Sleep Score (PSS) was developed by regressing sleep stages and efficiency (R-2 = 0.713) and, together with resting heart rate (RHR), was used as complementary indicator of physiological dimensions of sleep quality. With PSS and RHR, three distinct sleeper profiles were defined using k-means clustering: poor, resilient, and good sleepers. Six parameters differed significantly across clusters: nocturnal levels of temperature, illuminance, total volatile organic compounds and formaldehyde, and the daily mean level of exhaled CO2 and temperature. The cluster with resilient sleepers was characterized by slightly lower bedroom temperatures (-1.7 +/- 0.7 degrees C), along with 11.6 +/- 1.3 more minutes of deep sleep and 2.0 +/- 0.3% higher sleep efficiency. A mixed-effects model showed that female participants had 50% probability of being classified in the poor sleepers' cluster, whereas males and participants with PSQI<5 (indicating undisturbed sleep in the last month) had 59% and 45% probability of being classified in the resilient sleepers' cluster. Nocturnal bedroom environmental quality at night was identified as a key factor in shaping sleep quality, while continuous monitoring using wearable sensors provided valuable insights to draw useful conclusions to support well-being and comfort. Present outcomes demonstrate how integrating environmental and physiological monitoring can uncover sleeper profiles and support the design and operation of resilient, human-centric environments.

Continuous monitoring of personal exposures indoors and outdoors to assess human environmental resilience through sleep quality

Martins Gnecco V.
Writing – Original Draft Preparation
;
Pisello A. L.
Supervision
;
2026

Abstract

Understanding how environmental conditions influence human resilience is critical for designing climate-responsive buildings. Sleep quality represents a key human-centric indicator of environmental resilience, impacting cumulative exposure to different stimuli. This study presents an exploratory analysis of longitudinal monitoring data which examines how environmental exposures, physiological responses, and personal characteristics interact to shape human resilience through sleep quality in real-life settings. Sixteen participants were continuously monitored for ten days using wearable devices to collect physiological data and characterize environmental exposure patterns associated with sleep quality. A composite Predicted Sleep Score (PSS) was developed by regressing sleep stages and efficiency (R-2 = 0.713) and, together with resting heart rate (RHR), was used as complementary indicator of physiological dimensions of sleep quality. With PSS and RHR, three distinct sleeper profiles were defined using k-means clustering: poor, resilient, and good sleepers. Six parameters differed significantly across clusters: nocturnal levels of temperature, illuminance, total volatile organic compounds and formaldehyde, and the daily mean level of exhaled CO2 and temperature. The cluster with resilient sleepers was characterized by slightly lower bedroom temperatures (-1.7 +/- 0.7 degrees C), along with 11.6 +/- 1.3 more minutes of deep sleep and 2.0 +/- 0.3% higher sleep efficiency. A mixed-effects model showed that female participants had 50% probability of being classified in the poor sleepers' cluster, whereas males and participants with PSQI<5 (indicating undisturbed sleep in the last month) had 59% and 45% probability of being classified in the resilient sleepers' cluster. Nocturnal bedroom environmental quality at night was identified as a key factor in shaping sleep quality, while continuous monitoring using wearable sensors provided valuable insights to draw useful conclusions to support well-being and comfort. Present outcomes demonstrate how integrating environmental and physiological monitoring can uncover sleeper profiles and support the design and operation of resilient, human-centric environments.
2026
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1629521
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