The Accuracy, Night-to-Night Variability, and Stability of Frontopolar Sleep Electroencephalography Biomarkers

Abstract

Study Objectives: To assess the validity of sleep architecture and sleep continuity biomarkers obtained from a portable, multichannel forehead electroencephalography (EEG) recorder. Methods: Forty-seven subjects simultaneously underwent polysomnography (PSG) while wearing a multichannel frontopolar EEG recording device (Sleep Profiler). The PSG recordings independently staged by 5 registered polysomnographic technologists were compared for agreement with the autoscored sleep EEG before and after expert review. To assess the night-to-night variability and first night bias, 2 nights of self-applied, in-home EEG recordings obtained from a clinical cohort of 63 patients were used (41% with a diagnosis of insomnia/depression, 35% with insomnia/obstructive sleep apnea, and 17.5% with all three). The between-night stability of abnormal sleep biomarkers was determined by comparing each night's data to normative reference values. Results: The mean overall interscorer agreements between the 5 technologists were 75.9%, and the mean kappa score was 0.70. After visual review, the mean kappa score between the autostaging and five raters was 0.67, and staging agreed with a majority of scorers in at least 80% of the epochs for all stages except stage N1. Sleep spindles, autonomic activation, and stage N3 exhibited the least between-night variability (P < .0001) and strongest between-night stability. Antihypertensive medications were found to have a significant effect on sleep quality biomarkers (P < .02). Conclusions: A strong agreement was observed between the automated sleep staging and human-scored PSG. One night's recording appeared sufficient to characterize abnormal slow wave sleep, sleep spindle activity, and heart rate variability in patients, but a 2-night average improved the assessment of all other sleep biomarkers. Commentary: Two commentaries on this article appear in this issue on pages 771 and 773.

Effects of deep sedation on sleep in critically ill medical patients on mechanical ventilation

“…Overnight EEG recordings were made with the Sleep Profiler™ EEG Sleep Monitor (Advanced Brain Monitoring, Carlsbad, CA) (Levendowski et al., ). Snoring and environmental noise were measured with an acoustic microphone, whereas head movement and head position were derived from a triaxial accelerometer.…”

Machine‐learning‐derived sleep–wake staging from around‐the‐ear electroencephalogram outperforms manual scoring and actigraphy

“…These studies all showed promising results, but involved a limited number of participants and also restricted electrode positioning. Other user-mounted systems have been developed specifically for sleep (Levendowski et al, 2017;Younes, Soiferman, Thompson, & Giannouli, 2017Lucey et al, 2016Shambroom et al, 2012;Werth and Borbely, 1995), but these systems all require electrodes to be placed in highly visible locations. Ear-centered EEG solutions come with the benefit of being sufficiently discrete and therefore acceptable to users also for routine applications during the daytime.…”

Portable Sleep Monitoring Systems: Broadening the Horizons

“…A tangential but interesting and relevant finding reported by Levendowski et al 1 refers to the significantly more deteriorated sleep recorded in patients with insomnia on pharmacological therapy for elevated blood pressure. Compared to insomnia patients not taking antihypertensive medications, those on treatment presented increased light N2 and reduced N3 sleep stages, along with decreased delta, theta, alpha, and sigma spectral power and impaired autonomic activation in rapid eye movement (REM) sleep.…”

“…The validation study by Levendowski et al 1 presented in this issue of the Journal of Clinical Sleep Medicine expands upon the rapidly evolving field of portable technologies for home sleep testing. A mobile, multichannel electroencephalography (EEG) device was tested against standard polysomnography and results demonstrated acceptable consistency between automated sleep staging and manual scoring.…”