README.md

metadata

language: en
license: apache-2.0
tags:
  - sleep-staging
  - eeg
  - embeddings
  - physioex
  - chambon2018
pretty_name: Chambon2018 Embeddings
size_categories:
  - 1K<n<10K

Chambon2018 Embeddings

Pre-extracted per-epoch embeddings from Chambon2018 (Chambon et al. 2018), trained on MASS SS3 via PhysioEx.

Each subject directory contains:

• embeddings.npy — (n_epochs, 120) per-epoch embeddings (bfloat16)
• labels.npy — (n_epochs,) AASM sleep stage labels

Note: Chambon2018 is a per-epoch CNN encoder (no inter-epoch context). Embeddings are extracted directly without sliding-window voting.

Usage

from physioex.models import load_embeddings
path = load_embeddings("chambon2018", "hmc", verbose=True)

Linear Probe Results (5-fold subject-wise CV)

Dataset	Subjects	ACC	MF1	κ	F1-W	F1-N1	F1-N2	F1-N3	F1-REM
mass_ss05	26	0.8146	0.6653	0.7284	0.74	0.08	0.88	0.83	0.80
mass_ss02	19	0.7902	0.6397	0.6919	0.74	0.05	0.86	0.79	0.75
mass_ss03	62	0.7869	0.6638	0.6806	0.79	0.15	0.87	0.75	0.76
mass_ss04	40	0.7777	0.6353	0.6785	0.73	0.06	0.87	0.78	0.75
dcsm	255	0.7218	0.5239	0.5706	0.82	0.00	0.74	0.72	0.34
mass_ss01	53	0.7134	0.5899	0.5882	0.81	0.23	0.82	0.48	0.61
sleepedf	153	0.6001	0.4502	0.4198	0.65	0.00	0.72	0.52	0.36
hmc	151	0.5980	0.5099	0.4581	0.66	0.03	0.65	0.67	0.54

SHHS, MESA, HPAP, STAGES results pending (extraction running on Sofia HPC).

Model Details

• Architecture: Chambon2018 (Chambon et al. 2018) — braindecode SleepStagerChambon2018 per-epoch CNN
• Training data: MASS SS3 (62 subjects, single EEG channel at 128 Hz)
• Pipeline: raw (bandpass 0.3-40 Hz, resample 128 Hz)
• Sequence length: L=3 (central epoch classification)
• Embedding dim: 120

Datasets

Dataset	Source	URL
Sleep-EDF	PhysioNet	https://physionet.org/content/sleep-edfx/1.0.0/
HMC	PhysioNet	https://physionet.org/content/hmc-sleep-staging/1.1/
DCSM	ERDA/KU	https://erda.ku.dk/public/archives/db553715ecbe1f3ac66c1dc569826eef/published-archive.html
MASS	CEAMS	http://ceams-carsm.ca/mass/

Citations

@article{gagliardi2025physioex,
    author={Gagliardi, Guido and Alfeo, Luca and Cimino, Mario G C A and Valenza, Gaetano and De Vos, Maarten},
    title={PhysioEx, a new Python library for explainable sleep staging through deep learning},
    journal={Physiological Measurement},
    url={http://iopscience.iop.org/article/10.1088/1361-6579/adaf73},
    year={2025},
}

@article{chambon2018deep,
    title={A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series},
    author={Chambon, Stanislas and Galtier, Mathieu and Arnal, Pierrick and Wainrib, Gilles and Gramfort, Alexandre},
    journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering},
    year={2018},
}