0312 An At-home, Wireless, Sleep Monitoring System for Long-term, Reliable Sleep Assessment in Young and Older Adults

Abstract Introduction Poor sleep quality increases from middle age onward with impacts on cognition, most notably episodic memory, and is associated with an increased risk of Alzheimer’s disease (AD). There is great interest in determining if sleep quality, and what specific neural features thereof, may serve as a non-invasive biomarker of memory decline and AD. Constraints of “gold standard” polysomnography assessments of sleep’s neural architecture, including bulky, wired, rigid, expensive, and uncomfortable equipment either in a lab or at home, make collecting multiple nights of sleep data prohibitive. As night-to-night sleep variability predicts poorer cognition, it is essential to sample multiple nights from the comfort of home. Existing wearable devices enable sleep monitoring at home but remain bulky and rigid, or offer poor signal quality and inaccurate sleep analysis. Methods We deployed, in cognitively unimpaired young (age 18-36) and older (ages 60-74) adults, our recently developed and validated, inexpensive, gel-free, nearly weightless, sleep monitoring patch that uses soft, skin-conformable self-adhesive materials containing multiple laser-cut electrodes, self-applied to the face for optimal usability and comfort. Results Participants reported being easily able to self-apply the reusable sleep patch and operate the Bluetooth tablet-based data acquisition software throughout seven nights. Manual scoring and automated classification-based scoring showed high agreement across all sleep stages (82.43%, kappa value = 0.74). Signal-to-noise estimates of slow wave activity (0.5-3.75 Hz) show remarkable stability over the 7 nights in both young (SNR range 26.71 dB-33.42 dB, Cronbach’s alpha 0.797) and older (SNR range 26.27 dB-28.42 dB, Cronbach’s alpha 0.846) adults, comparable to estimates obtained from optimal conditions in our university sleep lab. Consistent with results from polysomnography, older adults showed reduced slow wave (N3) sleep (Young: 7.13 %; Older: 2.88 %). Conclusion This study validates that the high comfort, wearable patch can measure physiological sleep data at the level of clinical standards in adults across the lifespan. Future work will use this system to assess sleep-dependent consolidation across ages from the comfort of one’s home and measure sleep variables longitudinally to identify those most indicative of cognitive decline. Support (if any) This work was supported by the Alzheimer’s Association # FA00000633 and NIA # R21AG064309