# EESM23 · Ear-EEG Sleep Monitoring 2023: EEG decoding results

Five-stage sleep, in-ear and scalp

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 as** EESM23 · Ear-EEG Sleep Monitoring 2023 · OpenNeuro ds005178

Description sources [openneuro.org](https://openneuro.org/datasets/ds005178) · [doi.org](https://doi.org/10.18112/openneuro.ds005178.v1.0.0) · [pmc.ncbi.nlm.nih.gov](https://pmc.ncbi.nlm.nih.gov/articles/PMC11840015/)

## Where it appears

- [Can fewer electrodes, or electrodes in the ear, match a full scalp montage?](https://bci.report/topics/fewer-electrodes/)

## Published results

Every figure below is copied from a reviewed download, not recomputed for this page. Read each group with its protocol on the linked page.

### Fewer electrodes · in-ear vs. scalp sleep staging

Read with its protocol: [Fewer electrodes](https://bci.report/topics/fewer-electrodes/) · Chance level 20.0% · [evidence-update.json](https://bci.report/data/evidence-update.json)

**Balanced accuracy, 2 configurations.** Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

- 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%)

| 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

**Credit** Dataset: 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.

[CC0-1.0 ↗](https://creativecommons.org/publicdomain/zero/1.0/) · [Dataset record ↗](https://doi.org/10.18112/openneuro.ds005178.v1.0.0)

BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data belong to the people credited.

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Markdown copy of https://bci.report/datasets/eesm23/, generated from the published page. Figures are aggregate results; terms of use: https://bci.report/data-use/