Assessment of the suitability of using a forehead EEG electrode set and chin EMG electrodes for sleep staging in polysomnography
Abstract
Summary: Recently, a number of portable devices designed for full polysomnography at home have appeared. However, current scalp electrodes used for electroencephalograms are not practical for patient self‐application. The aim of this study was to evaluate the suitability of recently introduced forehead electroencephalogram electrode set and supplementary chin electromyogram electrodes for sleep staging. From 31 subjects (10 male, 21 female; age 31.3 ± 11.8 years), sleep was recorded simultaneously with a forehead electroencephalogram electrode set and with a standard polysomnography setup consisting of six recommended electroencephalogram channels, two electrooculogram channels and chin electromyogram. Thereafter, two experienced specialists scored each recording twice, based on either standard polysomnography or forehead recordings. Sleep variables recorded with the forehead electroencephalogram electrode set and separate chin electromyogram electrodes were highly consistent with those obtained with the standard polysomnography. There were no statistically significant differences in total sleep time, sleep efficiency or sleep latencies. However, compared with the standard polysomnography, there was a significant increase in the amount of stage N1 and N2, and a significant reduction in stage N3 and rapid eye movement sleep. Overall, epoch‐by‐epoch agreement between the methods was 79.5%. Inter‐scorer agreement for the forehead electroencephalogram was only slightly lower than that for standard polysomnography (76.1% versus 83.2%). Forehead electroencephalogram electrode set as supplemented with chin electromyogram electrodes may serve as a reliable and simple solution for recording total sleep time, and may be adequate for measuring sleep architecture. Because this electrode concept is well suited for patient's self‐application, it may offer a significant advancement in home polysomnography.
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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 [60]
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Masa, J. F., Corral, J., Pereira, R., Duran-Cantolla, J., Cabello, M., Hernandez-Blasco, L., Monasterio, C., Alonso, A., Chiner, E., Rubio, M., et al. (2011) · Thorax · doi:10.1136/thx.2010.152272 · Cited by 161 · see citing works
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The future of sleep health: a data-driven revolution in sleep science and medicine
Perez-Pozuelo, I., Zhai, B., Palotti, J., Mall, R., Aupetit, M., Garcia-Gomez, J. M., Taheri, S., Guan, Y., & Fernandez-Luque, L. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0244-4 · Cited by 311 · see citing works
Recent advances in wearable sensors and portable electronics for sleep monitoring
Kwon, S., Kim, H., & Yeo, W.-H. (2021) · iScience · doi:10.1016/j.isci.2021.102461 · Cited by 209 · see citing works
- Authors
- Myllymaa, S., Muraja‐Murro, A., Westeren‐Punnonen, S., Hukkanen, T., Lappalainen, R., Mervaala, E., Töyräs, J., Sipilä, K., & Myllymaa, K.
- Affiliations
- University of Eastern Finland (FI)
- Kuopio University Hospital (FI)
- Department of Clinical Neurophysiology Kuopio University Hospital Kuopio Finland
- Corresponding author
- Myllymaa, Sami
- Venue
- Journal of Sleep Research
- Publisher
- Wiley
- Published
- 2016-05-27
- Volume
- 25
- Issue
- 6
- Pages
- 636-645
- ISSN
- 0962-1105 (ISSN-L)
- 1365-2869
- OpenAlex
- W2406035465
- Cited by
- 66
- References
- 1
- Citations by year
- 2026: 4 · 2025: 8 · 2024: 6 · 2023: 3 · 2022: 5 · 2021: 14 · 2020: 10 · 2019: 9 · 2018: 2 · 2017: 4 · 2016: 1
- FWCI
- 3.39
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Sleep Research (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Suomen Kulttuurirahasto
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Health Sciences › Medicine › Physiology › Obstructive Sleep Apnea Research
- Keywords
- sleep stage classification, home polysomnography, home sleep monitoring, sleep architecture, REM sleep, NREM sleep stages
- MeSH terms
- Adult, Chin, Electrodes, Electroencephalography, Electromyography, Electrooculography, Female, Forehead, Humans, Male, Sleep Stages, Sleep, REM, Time Factors, Polysomnography
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