<p>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 <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\kappa = 0.77\)</EquationSource> </InlineEquation>). For daytime MWT trials, agreement was moderate (Cohen’s <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\kappa = 0.50\)</EquationSource> </InlineEquation>), 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 (<InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(n = 24\)</EquationSource> </InlineEquation>)—averaging across trials as in standard clinical practice—agreement was good (ICC = 0.71, <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(r = 0.75\)</EquationSource> </InlineEquation>, 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. </p><p>For overnight sleep architecture (<InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(n = 16\)</EquationSource> </InlineEquation> healthy controls), total sleep time (<InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(r = 0.94\)</EquationSource> </InlineEquation>, ICC = 0.85), sleep efficiency (<InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(r = 0.94\)</EquationSource> </InlineEquation>), and wake after sleep onset (<InlineEquation ID="IEq8"> <EquationSource Format="TEX">\(r = 0.93\)</EquationSource> </InlineEquation>) 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.</p>

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

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2026年5月22日

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

摘要

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 \(\kappa = 0.77\) ). For daytime MWT trials, agreement was moderate (Cohen’s \(\kappa = 0.50\) ), 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 ( \(n = 24\) )—averaging across trials as in standard clinical practice—agreement was good (ICC = 0.71, \(r = 0.75\) , 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 ( \(n = 16\) healthy controls), total sleep time ( \(r = 0.94\) , ICC = 0.85), sleep efficiency ( \(r = 0.94\) ), and wake after sleep onset ( \(r = 0.93\) ) 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.