README.md

metadata

language: en
license: apache-2.0
tags:
  - sleep-staging
  - eeg
  - pytorch
  - physioex
pretty_name: PhysioEx Pretrained Models

PhysioEx — Pretrained Sleep Staging Models

Pretrained deep learning models for automatic sleep staging from PhysioEx (Gagliardi et al. 2025).

All models follow the AASM 5-class standard: W, N1, N2, N3, REM.

Available Models

Model	Architecture	Training Dataset	Channels	Pipeline	Params	Reference
seqsleepnet-phan	BiLSTM + Attention	Sleep-EDF	EEG	seqsleepnet (STFT)	659K	Phan et al. 2019
tinysleepnet-supratak	CNN + LSTM	Sleep-EDF	EEG	raw	83K	Supratak & Guo 2020
sleeptransformer-phan	Transformer	SHHS	EEG	seqsleepnet (STFT)	2.1M	Phan et al. 2022
lseqsleepnet-phan	Long-sequence BiLSTM	SHHS	EEG	seqsleepnet (STFT)	1.8M	Phan et al. 2023
chambon2018	Braindecode CNN	MASS SS3	EEG	raw (128 Hz)	220K	Chambon et al. 2018
tsinalis-2016	2-layer CNN	Sleep-EDF	EEG	identity	145K	Tsinalis et al. 2016

Models are added as training completes. Check back for updates.

Usage

from physioex.models import load_from_pretrained

# Load a pretrained model
model = load_from_pretrained("seqsleepnet-phan", verbose=True)

# Use for inference or embedding extraction
from physioex.models import extract_embeddings, load_embeddings

# Extract embeddings on a new dataset
path = extract_embeddings(model, dataset, model_name="seqsleepnet-phan", ...)

# Or download pre-extracted embeddings from HuggingFace
path = load_embeddings("seqsleepnet-phan", "hmc", verbose=True)

Cross-Dataset Evaluation (SeqSleepNet-Phan)

Zero-shot transfer from Sleep-EDF to other datasets (voting evaluation):

Dataset	ACC	Macro F1	κ
Sleep-EDF (train)	0.8101	0.7575	0.7421
DCSM	0.6649	0.5839	0.5370
MESA	0.6330	0.5546	0.4921
MASS	0.6033	0.5422	0.4655
HMC	0.5851	0.5574	0.4464
WSC	0.4928	0.4577	0.3255
Parkinsons	0.4428	0.3902	0.2737
SHHS	0.3989	0.3597	0.2434
Alzheimers	0.2582	0.1449	0.0239

Pre-extracted Embeddings

Contextualized per-epoch embeddings are available as separate dataset repos:

Model	HuggingFace Repo	Datasets
SeqSleepNet-Phan	4rooms/seqsleepnet-phan-embeddings	20 datasets, 12.5K subjects

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
SHHS	NSRR	https://sleepdata.org/datasets/shhs
MESA	NSRR	https://sleepdata.org/datasets/mesa
HomePAP	NSRR	https://sleepdata.org/datasets/homepap
STAGES	NSRR	https://sleepdata.org/datasets/stages
MASS	CEAMS	http://ceams-carsm.ca/mass/
WSC	NSRR	https://sleepdata.org/datasets/wsc
MrOS	NSRR	https://sleepdata.org/datasets/mros

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{phan2019seqsleepnet,
    title={SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging},
    author={Phan, Huy and Andreotti, Fernando and Cooray, Navin and Chen, Oliver Y and De Vos, Maarten},
    journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering},
    year={2019},
}

@inproceedings{supratak2020tinysleepnet,
    title={TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG},
    author={Supratak, Akara and Guo, Yike},
    booktitle={IEEE EMBC},
    year={2020},
}

@article{phan2022sleeptransformer,
    title={SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty Quantification},
    author={Phan, Huy and Mikkelsen, Kaare and Ch\'en, Oliver Y and Koch, Philipp and Mertins, Alfred and De Vos, Maarten},
    journal={IEEE Transactions on Biomedical Engineering},
    year={2022},
}

@article{phan2023lseqsleepnet,
    title={L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep Staging},
    author={Phan, Huy and Ch\'en, Oliver Y and Koch, Philipp and Lu, Zhongxiang and McLoughlin, Ian and Mertins, Alfred and De Vos, Maarten},
    journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering},
    year={2023},
}

@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},
}

@article{tsinalis2016automatic,
    title={Automatic Sleep Stage Scoring with Single-Channel EEG Using Convolutional Neural Networks},
    author={Tsinalis, Orestis and Matthews, Paul M and Guo, Yike and Zafeiriou, Stefanos},
    journal={arXiv:1610.01683},
    year={2016},
}