Ear-EEG Sleep Monitoring 2023 (EESM23): at-home sleep recordings from 10 healthy participants by an Aarhus University group, each with two nights of combined ear-EEG and polysomnography followed by ten ear-EEG-only nights, using generic ear pieces with dry electrodes. Released on OpenNeuro as ds005178 (CC0) and described in Scientific Data (2025).
Also known asEESM23 · Ear-EEG Sleep Monitoring 2023 · OpenNeuro ds005178
Log-bandpower logistic regression · Four in-ear channels
53.6% (47.4%–59.7%)
Log-bandpower logistic regression · Six scalp electrodes
69.0% (63.4%–74.2%)
0%25%50%75%100%
Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line, where drawn: chance level.
Method
Condition
Metric
Value
People
Log-bandpower logistic regression
Four in-ear channels
Balanced accuracy
53.6%47.4%–59.7%
10
Log-bandpower logistic regression
Six scalp electrodes
Balanced accuracy
69.0%63.4%–74.2%
10
Log-bandpower logistic regression
Scalp minus in-ear, same epochs
Paired difference
+15.4 pp+10.6 pp–+20.3 pp
10
Source and licence
EESM23 · Ear-EEG Sleep Monitoring 2023
CreditDataset: Yousef Rezaei Tabar, Kaare Mikkelsen, Laura Birch, Nelly Shenton, Simon L. Kappel, Astrid R. Bertelsen, Reza Nikbakht, Hans O. Toft, Chris H. Henriksen, Martin C. Hemmsen, Mike L. Rank, Marit Otto and Preben Kidmose · Ear-EEG Sleep Monitoring 2023 (EESM23), OpenNeuro ds005178 v1.0.0, doi:10.18112/openneuro.ds005178.v1.0.0. Study: 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 and Preben Kidmose · Ear-EEG sleep monitoring data sets, Scientific Data 12, 301 (2025), doi:10.1038/s41597-025-04579-8. Processed export: Zachary1150/EESM23-Processed on Hugging Face, which did not create the original cohort.
BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data remain their creators’.
BCI Report