0310 Multi-center Evaluation of a User Operable EEG Based Automated Sleep Monitor

Abstract Introduction Sleep pathology is increasingly being recognized in many neuropsychiatric conditions, including those not traditionally associated with sleep medicine. Improved therapeutic strategies will benefit from EEG-based sleep analytics, but EEG is limited by cost and availability. Here we evaluate the performance and usability of a user operated dry-EEG electrode-based sleep monitoring headband (the Dreem 3S, D3S), which is intended to provide detailed brain EEG activity with automated sleep staging and longitudinal recording ability from the home environment. Methods Two prospective studies included 60 subjects who underwent either one overnight in-lab traditional polysomnography (PSG) while concomitantly wearing the D3S, or three nights at home with the D3S. At home, subjects self-applied the D3S. Device usability and automated sleep staging performance were evaluated. Results Overall agreement between D3S and PSG scoring was 85.6% across sleep stages. Intra Class Correlation (ICC) for Total Sleep Time (TST), Sleep Efficiency (SE), Latency to Persistent Sleep (LPS), and Wake After Sleep Onset (WASO) exceeded 90%, indicating excellent agreement between D3S and PSG. ICC ranged from 65% to 86% for automated machine learning interpretation of time spent in N1, N2, N3, and REM, comparable or superior to other devices and individual human performance. Usability evaluation demonstrated safe and comfortable use of the device in the home setting, with a System Usability Score (SUS) score of ≥ 68. Subjects were able to operate and record 2-3 nights of high-quality data without additional support or technologist intervention. Furthermore, 96.6% of each record was deemed to be of sufficient EEG signal quality to enable manual expert review. Conclusion The Dreem 3S provided accurate sleep-staging and sleep metrics from EEG data acquired in conjunction with in-lab PSG or multiple nights in the home setting. Results were comparable to in-lab PSG results. D3S therefore offers objective EEG-based sleep investigation that is not feasible with traditional PSG, such as longitudinal data acquisition in a patient’s home environment without need for expert technologist applications. Such technology enables expansion of EEG-based sleep analysis for novel conditions. Support (if any) This work was supported by Beacon Biosignals, which is a private company with ownership of the D3S.