Using wearable EEG to examine age trends in sleep macro- and micro-architecture across adolescence

Abstract

Adolescence is a period of distinct maturational changes in sleep physiology. Age-related trends in sleep physiology have been captured using laboratory-based polysomnography, a method limited by logistical burden and high cost. We tested the ability of the accessible Dreem3 sleep EEG headband to replicate established age effects in sleep physiology from late childhood through early adulthood. Typically developing youth (N=100, 9-26 years) completed 3-4 consecutive nights of at-home sleep recording. We estimated age-related trends across eight macro-architecture and 15 micro-architecture variables with known age effects, and conducted exploratory analyses of 24 additional variables. Dreem replicated established age trends, including increases in non-rapid eye movement (NREM) stage 2, and decreases in N3, time in bed, NREM delta and theta power with increasing age. Exploratory analysis revealed age effects in twelve variables, including decreases in spindle activity with increasing age. Sleep EEG wearables offer an accessible way to characterize sleep physiology development.