Wearable In-Ear Encephalography Sensor for Monitoring Sleep. Preliminary Observations from Nap Studies
Open accessAbstract
Rationale: To date, EEG is the only quantifiable measure of the neural changes that define sleep. Although it is used widely for clinical testing, scalp-electrode EEG is costly and is poorly tolerated by sleeping patients. Objectives: This was a pilot study to assess the agreement between EEG recordings obtained from a new ear-EEG sensor and those obtained simultaneously from standard scalp electrodes. Methods: Participants were four healthy men, 25 to 36 years of age. During naps, EEG tracings were recorded simultaneously from the ear sensor and from standard scalp electrodes. A clinical expert, blinded to the data collection, analyzed 30-second epochs of recordings from both devices, using standardized criteria. The agreement between scalp- and ear-recordings was assessed. Measurements and Main Results: We scored 360 epochs (scalp-EEG and ear-EEG), of which 254 (70.6%) were scored as non–REM sleep using scalp-EEG. The ear-EEG sensor had a sensitivity of 0.88 (95% confidence interval [CI], 0.82–0.92) and a specificity of 0.78 (95% CI, 0.70–0.84) in detecting N2/N3 sleep. The kappa coefficient between the scalp- and the ear-EEG was 0.65 (95% CI, 0.58–0.73). As a sleep monitor (all non–REM sleep stages vs. wake), the in-ear sensor had a sensitivity of 0.91 (95% CI, 0.87–0.94) and a specificity of 0.66 (95% CI, 0.56–0.75). The kappa coefficient was 0.60 (95% CI, 0.50–0.69). Conclusions: Substantial agreement was observed between recordings derived from a new ear-EEG sensor and conventional scalp electrodes on four healthy volunteers during daytime naps.
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Several miniaturised EEG devices have shown promising results with regards to their ability to classify sleep stages.
“Similarly, several miniaturised EEG devices have shown promising results with regards to their ability to classify sleep stages60,61.”
From The future of sleep health: a data-driven revolution in sleep science and medicine (2020) · cites this paper as [61]
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Chan, A. H. W., Emadi, R. C., Lin, A., Schroeder, M. J., Singh, R., Shaik, R., George, M. C., Gomberg, J., Eka, O., Kavanagh, T., et al. (2026) · Sensors · doi:10.3390/s26196343
- Authors
- Looney, D., Goverdovsky, V., Rosenzweig, I., Morrell, M. J., & Mandic, D. P.
- Affiliations
- Communications and Signal Processing Group, Electrical and Electronic Engineering Department
- National Health Service (GB)
- Corresponding author
- Mandic, Danilo P.
- Venue
- Annals of the American Thoracic Society
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-12-01
- Volume
- 13
- Issue
- 12
- Pages
- 2229-2233
- ISSN
- 2325-6621 (ISSN-L)
- 2329-6933
- PMC
- PMC5291497
- OpenAlex
- W2525723775
- Cited by
- 78
- References
- 17
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 9 · 2023: 9 · 2022: 8 · 2021: 6 · 2020: 10 · 2019: 8 · 2018: 13 · 2017: 7
- FWCI
- 5.94
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Annals of the American Thoracic Society (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Research Portal (King's College London) (publishedVersion, other-oa)
- Spiral (Imperial College London) (submittedVersion)
- Funders
- Wellcome Trust (103952/Z/14/Z)
- National Institute for Health and Care Research (08/56/02)
- Rosetrees Trust
- Engineering and Physical Sciences Research Council (EP/K025643, EP/K025643/1)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Keywords
- ear-EEG, sleep monitoring, NREM sleep, sleep stage classification
- MeSH terms
- Wearable Electronic Devices, Adult, Electroencephalography, United Kingdom, Humans, Male, Monitoring, Physiologic, Pilot Projects, Sensitivity and Specificity, Sleep Stages, Healthy Volunteers
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