BOAS · Bitbrain Open Access Sleep dataset: EEG decoding results

Name: BCI Report: results on BOAS · Bitbrain Open Access Sleep dataset
Creator: BCI Report
License: https://creativecommons.org/licenses/by/4.0/

Overnight sleep, six polysomnography EEG channels, human-consensus stages

BOAS · Bitbrain Open Access Sleep dataset: EEG decoding results

BOAS, the Bitbrain Open Access Sleep dataset (OpenNeuro ds005555), holds 128 full-night recordings from 100 adults of the general population, each recorded with clinical polysomnography and a Bitbrain forehead headband at the same time. Sleep stages were scored by three human experts, a fourth breaking three-way ties, and separately by the publisher's automatic model. Released by Bitbrain Technologies (Zaragoza, Spain) and colleagues under CC0; version 1.1.3 is used here. No peer-reviewed paper describes the dataset. Only the six polysomnography EEG channels and the human-consensus stages are used here.

Also known as BOAS · Bitbrain Open Access Sleep dataset · The Bitbrain Open Access Sleep (BOAS) dataset · OpenNeuro ds005555 · ds005555

Description sources openneuro.org · api.datacite.org · www.bitbrain.com

Where it appears

Can one EEG model answer several questions about the same data as well as separate models, and at what cost?

Published results

Every figure below is copied from a reviewed download, not recomputed for this page.

One model, several questions · sleep (route 2)

Read with its protocol: One model, several questions · shared-representation-update.json

Method	Condition	Metric	Value	People
EEGNet	fixed heads (B-lin) · sleep stage, five stages (SL-A) · trained from scratch, three seeds	Balanced accuracy	34.4%32.1%–37.0%	100
EEGNet	shared hidden layer (B-sh) · sleep stage, five stages (SL-A) · trained from scratch, three seeds	Balanced accuracy	42.9%40.1%–45.7%	100
EEGNet	question-conditioned head (C1) · sleep stage, five stages (SL-A) · trained from scratch, three seeds	Balanced accuracy	41.4%38.6%–44.2%	100
EEGNet	separate model (A) · sleep stage, five stages (SL-A) · trained from scratch, three seeds	Balanced accuracy	35.3%32.9%–37.8%	100
EEGNet	sleep stage, five stages (SL-A) · conditioned head minus fixed heads (C1 − B-lin)	Paired difference, balanced accuracy	+6.96 pp+4.92–+9.09 ppC1 higher; 2 pp margin not met; gate passed.	100
EEGNet	sleep stage, five stages (SL-A) · conditioned head minus the same layer not told the question (C1 − B-sh)	Paired difference, balanced accuracy	−1.47 pp−3.79–+0.94 ppNo difference shown; B-sh non-inferior at 2 pp; gate passed.	100
EEGNet	sleep stage, five stages (SL-A) · fixed heads on one shared small-CNN trunk minus separate models (B-lin − A(SL-A))	Paired difference, balanced accuracy	−0.84 pp−2.73–+0.91 ppNo difference shown; 2 pp margin not met: inconclusive at this sample size; gate passed.	100
CBraMod	fixed heads (B-lin-fz-sgd) · sleep stage, five stages (SL-A) · heads on frozen features, three seeds	Balanced accuracy	70.7%68.5%–72.7%	100
CBraMod	shared hidden layer (B-sh-fz) · sleep stage, five stages (SL-A) · heads on frozen features, three seeds	Balanced accuracy	71.4%69.1%–73.6%	100
CBraMod	question-conditioned head (C1-fz) · sleep stage, five stages (SL-A) · heads on frozen features, three seeds	Balanced accuracy	70.9%68.6%–73.0%	100
CBraMod	sleep stage, five stages (SL-A) · conditioned head minus fixed heads, on frozen CBraMod features (C1-fz − B-lin-fz-sgd)	Paired difference, balanced accuracy	+0.19 pp−0.74–+1.14 ppNo difference shown; equivalent within ±2 pp; gate passed.	100
EEGNet	fixed heads (B-lin) · next epoch’s stage differs (SL-E) · trained from scratch, three seeds	Balanced accuracy	54.4%53.5%–55.4%	100
EEGNet	shared hidden layer (B-sh) · next epoch’s stage differs (SL-E) · trained from scratch, three seeds	Balanced accuracy	58.9%57.5%–60.2%	100
EEGNet	question-conditioned head (C1) · next epoch’s stage differs (SL-E) · trained from scratch, three seeds	Balanced accuracy	57.5%56.0%–58.8%	100
EEGNet	separate model (A) · next epoch’s stage differs (SL-E) · trained from scratch, three seeds	Balanced accuracy	53.2%52.2%–54.3%	100
EEGNet	next epoch’s stage differs (SL-E) · conditioned head minus fixed heads (C1 − B-lin)	Paired difference, balanced accuracy	+3.02 pp+1.55–+4.35 ppC1 higher; 2 pp margin not met (not read: at floor); at floor: reported, not counted.	100
EEGNet	next epoch’s stage differs (SL-E) · conditioned head minus the same layer not told the question (C1 − B-sh)	Paired difference, balanced accuracy	−1.41 pp−2.40–−0.50 ppB-sh higher; B-sh non-inferior at 2 pp (not read: at floor); at floor: reported, not counted.	100
EEGNet	next epoch’s stage differs (SL-E) · fixed heads on one shared small-CNN trunk minus separate models (B-lin − A(SL-E))	Paired difference, balanced accuracy	+1.20 pp+0.07–+2.44 ppB-lin higher; B-lin non-inferior at 2 pp (not read: at floor); at floor: reported, not counted.	100
CBraMod	fixed heads (B-lin-fz-sgd) · next epoch’s stage differs (SL-E) · heads on frozen features, three seeds	Balanced accuracy	63.5%62.3%–64.7%	100
CBraMod	shared hidden layer (B-sh-fz) · next epoch’s stage differs (SL-E) · heads on frozen features, three seeds	Balanced accuracy	65.5%64.1%–66.7%	100
CBraMod	question-conditioned head (C1-fz) · next epoch’s stage differs (SL-E) · heads on frozen features, three seeds	Balanced accuracy	65.2%63.9%–66.5%	100
CBraMod	next epoch’s stage differs (SL-E) · conditioned head minus fixed heads, on frozen CBraMod features (C1-fz − B-lin-fz-sgd)	Paired difference, balanced accuracy	+1.75 pp+0.92–+2.63 ppC1-fz higher; 2 pp margin not met; gate passed.	100
EEGNet	fixed heads (B-lin) · first or second half of the night (SL-F) · trained from scratch, three seeds	Balanced accuracy	54.2%53.0%–55.6%	100
EEGNet	shared hidden layer (B-sh) · first or second half of the night (SL-F) · trained from scratch, three seeds	Balanced accuracy	55.8%54.2%–57.4%	100
EEGNet	question-conditioned head (C1) · first or second half of the night (SL-F) · trained from scratch, three seeds	Balanced accuracy	55.6%54.2%–57.1%	100
EEGNet	separate model (A) · first or second half of the night (SL-F) · trained from scratch, three seeds	Balanced accuracy	52.2%51.0%–53.7%	100
EEGNet	first or second half of the night (SL-F) · conditioned head minus fixed heads (C1 − B-lin)	Paired difference, balanced accuracy	+1.42 pp−0.25–+2.90 ppNo difference shown; 2 pp margin not met (not read: at floor): inconclusive at this sample size; at floor: reported, not counted.	100
EEGNet	first or second half of the night (SL-F) · conditioned head minus the same layer not told the question (C1 − B-sh)	Paired difference, balanced accuracy	−0.14 pp−1.41–+1.15 ppNo difference shown; equivalent within ±2 pp (not read: at floor); at floor: reported, not counted.	100
EEGNet	first or second half of the night (SL-F) · fixed heads on one shared small-CNN trunk minus separate models (B-lin − A(SL-F))	Paired difference, balanced accuracy	+2.01 pp+0.54–+3.89 ppB-lin higher; B-lin non-inferior at 2 pp (not read: at floor); at floor: reported, not counted.	100
CBraMod	fixed heads (B-lin-fz-sgd) · first or second half of the night (SL-F) · heads on frozen features, three seeds	Balanced accuracy	64.5%62.8%–66.1%	100
CBraMod	shared hidden layer (B-sh-fz) · first or second half of the night (SL-F) · heads on frozen features, three seeds	Balanced accuracy	65.2%63.6%–66.9%	100
CBraMod	question-conditioned head (C1-fz) · first or second half of the night (SL-F) · heads on frozen features, three seeds	Balanced accuracy	65.2%63.6%–66.9%	100
CBraMod	first or second half of the night (SL-F) · conditioned head minus fixed heads, on frozen CBraMod features (C1-fz − B-lin-fz-sgd)	Paired difference, balanced accuracy	+0.77 pp−0.14–+1.67 ppNo difference shown; equivalent within ±2 pp; gate passed.	100
EEGNet	awake or asleep (SL-B) · its own model, A(SL-B), against reading it off A(SL-A)	log R, the dedicated model’s remaining error over the read-out’s	−0.380−0.583–−0.203Dedicated model leaves less error; 20% margin not met; gate passed.	100

BOAS is published with three stated gaps (owner decision, 7 October 2026):

The consent statement does not say whether participants agreed to public sharing or secondary use.
The ethics and consent statements come from the publisher's dataset description and README. No peer-reviewed paper describes BOAS.
The ethics reference was added to the release in version 1.1.1 (May 2025), and the release does not say when it was granted relative to the recordings.

Participants are pseudonymised in the public release. No result here evaluates Bitbrain's headband or its automatic sleep scoring; neither is used.

Credit: Eduardo López-Larraz, María Sierra-Torralba, Sergio Clemente, Galit Fierro, David Oriol, Javier Minguez, Luis Montesano and Jens G. Klinzing · The Bitbrain Open Access Sleep (BOAS) dataset, OpenNeuro ds005555, version 1.1.3 (2026), doi:10.18112/openneuro.ds005555.v1.1.3. Polysomnography EEG and the human-consensus stage labels only; the headband recordings and the publisher's automatic labels are not used.

What these figures cannot say: The questions are label-backed classification targets from one dataset each, asked by identifier. They are not language prompts and say nothing about unseen questions (route 3). Per-person balanced accuracy averages people equally; it compares arms and is not a deployment error rate. SL-E and SL-F are largely predictable from the current stage: read off the true current stage alone, they reach 61.9% and 59.2% balanced accuracy (100 people; descriptive). A contrast shows a difference when its paired 95% interval excludes zero; it is equivalent when the whole interval lies within ±2 pp, the margin fixed before any result, and an arm is non-inferior when the interval rules out its being 2 pp or more behind. No multiplicity correction: across route 2’s 21 primary comparisons and its secondary ones, about one in 20 comparisons with no true difference may show one by chance. No ranking where intervals overlap. Every limitation of route 2 →

Source and licence

BOAS · Bitbrain Open Access Sleep dataset

Credit Eduardo López-Larraz, María Sierra-Torralba, Sergio Clemente, Galit Fierro, David Oriol, Javier Minguez, Luis Montesano and Jens G. Klinzing · The Bitbrain Open Access Sleep (BOAS) dataset, OpenNeuro ds005555, version 1.1.3 (2026), doi:10.18112/openneuro.ds005555.v1.1.3. Polysomnography EEG and the human-consensus stage labels only; the headband recordings and the publisher's automatic labels are not used.

CC0-1.0 ↗ · Dataset record ↗

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.

Ethics and consent, as the publisher states them

The dataset description states approval by the Comité de Ética de la Investigación de la Comunidad Autónoma de Aragón (C.I. PI24/046).

The README states that participants, adult members of the general population, provided written informed consent.

The owner approved publishing BOAS cohort aggregates with stated gaps on 2026-10-07; the three gaps are printed with the results above. Participants are pseudonymised in the public release.

All datasets → · All methods →

Cite this page

BCI Report (2026). BOAS · Bitbrain Open Access Sleep dataset: EEG decoding results. https://bci.report/datasets/boas/

Figures from release shared-representation-update-20261007 (2026-10-07). Cite the upstream dataset as well: its credit is on this page.

Every release is archived on Zenodo: doi:10.5281/zenodo.23123296. BibTeX for the site and its releases → · CITATION.cff ↗