Ear-EEG sleep monitoring data sets

Kaare Bjarke Mikkelsen; Yousef Rezai Tabar; Laura Rævsbæk Birch; Simon Lind Kappel; Christian Bech Christensen; Lars Dalskov Mosgaard; Marit Otto; Martin Christian Hemmsen; Mike Lind Rank; Preben Kidmose

doi:10.1038/s41597-025-04579-8

Ear-EEG sleep monitoring data sets

Kaare Bjarke Mikkelsen^*
, Yousef Rezai Tabar
, Laura Rævsbæk Birch
, Simon Lind Kappel
, Christian Bech Christensen
, Lars Dalskov Mosgaard
, Marit Otto
, Martin Christian Hemmsen
, Mike Lind Rank
, Preben Kidmose

^*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

2 Citationer (Scopus)

Abstract

Here we present data from two studies, both of which had the purpose of investigating the potential of using electroencephalograms measured from the ear (’ear-EEG’) for sleep monitoring in a home environment. In total, 320 nights were recorded. All nights were recorded with ear-EEG, and some were also recorded using scalp-EEG and/or wristworn actigraphy. All subjects were recorded multiple times. To our knowledge, this is the most extensive open access data set available for mobile EEG development, and possibly also the best open access dataset for studying repeated sleep monitoring on individuals. We describe the details of each data set, including data quality measures, and compare the sleep scoring performance to a previously published dataset.

Originalsprog	Engelsk
Artikelnummer	301
Tidsskrift	Scientific Data
Vol/bind	12
Nummer	1
ISSN	2052-4463
DOI	https://doi.org/10.1038/s41597-025-04579-8
Status	Udgivet - dec. 2025

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10.1038/s41597-025-04579-8Licens: CC BY-NC-ND

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abstract = "Here we present data from two studies, both of which had the purpose of investigating the potential of using electroencephalograms measured from the ear ({\textquoteright}ear-EEG{\textquoteright}) for sleep monitoring in a home environment. In total, 320 nights were recorded. All nights were recorded with ear-EEG, and some were also recorded using scalp-EEG and/or wristworn actigraphy. All subjects were recorded multiple times. To our knowledge, this is the most extensive open access data set available for mobile EEG development, and possibly also the best open access dataset for studying repeated sleep monitoring on individuals. We describe the details of each data set, including data quality measures, and compare the sleep scoring performance to a previously published dataset.",

author = "\{Bjarke Mikkelsen\}, Kaare and \{Rezai Tabar\}, Yousef and \{R{\ae}vsb{\ae}k Birch\}, Laura and Kappel, \{Simon Lind\} and Christensen, \{Christian Bech\} and \{Dalskov Mosgaard\}, Lars and Marit Otto and \{Christian Hemmsen\}, Martin and \{Lind Rank\}, Mike and Preben Kidmose",

year = "2025",

month = dec,

doi = "10.1038/s41597-025-04579-8",

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AU - Bjarke Mikkelsen, Kaare

AU - Rezai Tabar, Yousef

AU - Rævsbæk Birch, Laura

AU - Kappel, Simon Lind

AU - Christensen, Christian Bech

AU - Dalskov Mosgaard, Lars

AU - Otto, Marit

AU - Christian Hemmsen, Martin

AU - Lind Rank, Mike

AU - Kidmose, Preben

PY - 2025/12

Y1 - 2025/12

N2 - Here we present data from two studies, both of which had the purpose of investigating the potential of using electroencephalograms measured from the ear (’ear-EEG’) for sleep monitoring in a home environment. In total, 320 nights were recorded. All nights were recorded with ear-EEG, and some were also recorded using scalp-EEG and/or wristworn actigraphy. All subjects were recorded multiple times. To our knowledge, this is the most extensive open access data set available for mobile EEG development, and possibly also the best open access dataset for studying repeated sleep monitoring on individuals. We describe the details of each data set, including data quality measures, and compare the sleep scoring performance to a previously published dataset.

AB - Here we present data from two studies, both of which had the purpose of investigating the potential of using electroencephalograms measured from the ear (’ear-EEG’) for sleep monitoring in a home environment. In total, 320 nights were recorded. All nights were recorded with ear-EEG, and some were also recorded using scalp-EEG and/or wristworn actigraphy. All subjects were recorded multiple times. To our knowledge, this is the most extensive open access data set available for mobile EEG development, and possibly also the best open access dataset for studying repeated sleep monitoring on individuals. We describe the details of each data set, including data quality measures, and compare the sleep scoring performance to a previously published dataset.

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DO - 10.1038/s41597-025-04579-8

M3 - Journal article

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AN - SCOPUS:85219138941

SN - 2052-4463

VL - 12

JO - Scientific Data

JF - Scientific Data

IS - 1

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ER -

Ear-EEG sleep monitoring data sets

Abstract

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