A novel, wearable, in-ear EEG technology to assess sleep and daytime sleepiness

In-ear electroencephalography (EEG) has emerged as a promising alternative to traditional in-laboratory sleep studies, offering greater comfort and practicality. Here we present a novel in-ear EEG system, comparing in-ear recordings against scalp EEG channels acquired concurrently as part of polysomnography (PSG). The study enrolled 16 healthy control participants in a single-visit overnight-plus-daytime design, and 8 participants with central disorders of hypersomnolence (CDH) in a randomized crossover daytime design (medication vs. medication-holiday). For overnight sleep recordings, ear-EEG and scalp EEG sleep staging showed substantial agreement (Cohen's [Formula: see text]). For daytime MWT trials, agreement was moderate (Cohen's [Formula: see text]), reflecting the predominance of wake epochs in this paradigm. For the primary Maintenance of Wakefulness Test (MWT) endpoint of sleep onset latency (SOL), at the per-subject level ([Formula: see text])-averaging across trials as in standard clinical practice-agreement was good (ICC = 0.71, [Formula: see text], MAD = 5.1 min). Among the 37 of 126 trials where both devices detected sleep (approximately 30% of trials), agreement was strong (ICC = 0.82, MAD = 1.9 min), with excellent agreement in healthy controls (ICC = 0.95, MAD = 1.2 min). Overall trial-level agreement across all 126 trials was moderate (ICC = 0.55), reflecting 22 discordant trials in which scalp EEG detected sleep but in-ear EEG did not-predominantly brief, subtle N1 transitions, concentrated in a subset of CDH participants. For overnight sleep architecture ([Formula: see text] healthy controls), total sleep time ([Formula: see text], ICC = 0.85), sleep efficiency ([Formula: see text]), and wake after sleep onset ([Formula: see text]) showed strong agreement, with small systematic biases consistent with reduced N1 detection sensitivity. These findings support the feasibility of in-ear EEG for sleep staging and daytime sleepiness assessment in laboratory settings, and motivate larger confirmatory studies-including home-based longitudinal monitoring-to establish clinical utility, particularly in populations with altered sleep architecture.

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Publication Details

Journal
Bioelectronic Medicine
Published
2026-05-21
DOI
https://doi.org/10.1186/s42234-026-00207-x
Primary Topic
Sleep and Work-Related Fatigue
Type
article
Field-Weighted Citation Impact
0.00

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article

A novel, wearable, in-ear EEG technology to assess sleep and daytime sleepiness

Jonathan Berent, Derek L. Buhl, Akshay Paul, David B. Rye et al.
Bioelectronic Medicine
Sleep and Work-Related Fatigue
article

A novel, wearable, in-ear EEG technology to assess sleep and daytime sleepiness

Jonathan Berent, Derek L. Buhl, Akshay Paul, David B. Rye, Brian Tracey, K. Borodin, C. Dong, Prabhjyot Saini, Dmitri Volfson, Andrew X. Stewart, Devansh Bheda
article en

Abstract

In-ear electroencephalography (EEG) has emerged as a promising alternative to traditional in-laboratory sleep studies, offering greater comfort and practicality. Here we present a novel in-ear EEG system, comparing in-ear recordings against scalp EEG channels acquired concurrently as part of polysomnography (PSG). The study enrolled 16 healthy control participants in a single-visit overnight-plus-daytime design, and 8 participants with central disorders of hypersomnolence (CDH) in a randomized crossover daytime design (medication vs. medication-holiday). For overnight sleep recordings, ear-EEG and scalp EEG sleep staging showed substantial agreement (Cohen's [Formula: see text]). For daytime MWT trials, agreement was moderate (Cohen's [Formula: see text]), reflecting the predominance of wake epochs in this paradigm. For the primary Maintenance of Wakefulness Test (MWT) endpoint of sleep onset latency (SOL), at the per-subject level ([Formula: see text])-averaging across trials as in standard clinical practice-agreement was good (ICC = 0.71, [Formula: see text], MAD = 5.1 min). Among the 37 of 126 trials where both devices detected sleep (approximately 30% of trials), agreement was strong (ICC = 0.82, MAD = 1.9 min), with excellent agreement in healthy controls (ICC = 0.95, MAD = 1.2 min). Overall trial-level agreement across all 126 trials was moderate (ICC = 0.55), reflecting 22 discordant trials in which scalp EEG detected sleep but in-ear EEG did not-predominantly brief, subtle N1 transitions, concentrated in a subset of CDH participants. For overnight sleep architecture ([Formula: see text] healthy controls), total sleep time ([Formula: see text], ICC = 0.85), sleep efficiency ([Formula: see text]), and wake after sleep onset ([Formula: see text]) showed strong agreement, with small systematic biases consistent with reduced N1 detection sensitivity. These findings support the feasibility of in-ear EEG for sleep staging and daytime sleepiness assessment in laboratory settings, and motivate larger confirmatory studies-including home-based longitudinal monitoring-to establish clinical utility, particularly in populations with altered sleep architecture.

Bioelectronic MedicineVol. 12(1)
Emory University (US), Universidade Paranaense (BR), Takeda (United States) (US), NextInput (United States) (US), Indus University (IN)
Takeda Development Center Americas
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Sleep and Work-Related Fatigue
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