The impact of stress on sleep architecture: A seven-day study leveraging a psychophysiological stress detection algorithm and wearable EEG

Objectives: Stress is known to be a modifiable key determinant of sleep quality. This study aims to investigate the impact of daytime physiological stress and nighttime environmental stressors on sleep architecture using a rule-based algorithm and wearable sensors in a real-world setting. Methods: Twenty-one participants in Jerusalem were monitored over a 7-day period using the Dreem Headband, a wearable device that measures sleep via electroencephalography. Daytime stress was quantified through the Moment of Stress algorithm, utilizing electrodermal activity from the Empatica Embrace Plus bracelet. To assess potential sources of nighttime stress, we used indoor sensors to measure noise and temperature levels in the bedroom. We applied linear mixed-effects models with a random intercept at the individual level to assess the effects of these factors on sleep outcomes. Results: An increase in the number of Moments of Stress per day from the 10th to the 90th percentile was related to a 6.57-point increase in the rapid eye movement (REM) sleep percentage and a 5.74-point decrease in the deep (N3) sleep percentage, indicating a shift in sleep architecture under heightened stress. Each additional minute of noise exposure above 65 dB(A) was linked to 1.20 more minutes of wake after sleep onset (WASO) (95% CI: 0.54-1.86) and to a 0.10-point increase in light (N1) sleep percentage (95% CI: 0.03-0.16). No association was detected between temperature and sleep. Conclusions: Overall, these preliminary findings suggest that daytime physiological stress and nighttime noise may be associated with alterations in sleep architecture in naturalistic settings.