---
language: en
license: apache-2.0
tags:
  - sleep-staging
  - eeg
  - embeddings
  - physioex
  - tsinalis
pretty_name: Tsinalis-2016 Embeddings
size_categories:
  - 10K<n<100K
---

# Tsinalis-2016 Embeddings

Pre-extracted per-epoch embeddings from **TsinalisCNN** (Tsinalis et al. 2016),
trained on Sleep-EDF via [PhysioEx](https://github.com/guidogagl/physioex).

Each subject directory contains:
- `embeddings.npy` — `(n_epochs, 500)` per-epoch embeddings (bfloat16)
- `labels.npy` — `(n_epochs,)` AASM sleep stage labels

**Note:** Tsinalis concatenates L=5 epochs before convolution. Embeddings are
extracted using centered windows (each epoch gets the feature vector from the
window centered on it).

## Usage

```python
from physioex.models import load_embeddings
path = load_embeddings("tsinalis-2016", "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 |
|---|---|---|---|---|---|---|---|---|---|
| sleepedf | 153 | **0.8297** | **0.7563** | **0.7631** | 0.93 | 0.41 | 0.86 | 0.80 | 0.78 |
| mass_ss05 | 26 | 0.8157 | 0.7004 | 0.7297 | 0.72 | 0.26 | 0.87 | 0.82 | 0.83 |
| mass_ss02 | 19 | 0.8062 | 0.6925 | 0.7134 | 0.70 | 0.28 | 0.87 | 0.83 | 0.78 |
| mass_ss03 | 62 | 0.7950 | 0.7039 | 0.6923 | 0.77 | 0.33 | 0.87 | 0.76 | 0.80 |
| mass_ss04 | 40 | 0.7842 | 0.6791 | 0.6865 | 0.73 | 0.24 | 0.86 | 0.79 | 0.77 |
| mass_ss01 | 53 | 0.7473 | 0.6691 | 0.6388 | 0.83 | 0.36 | 0.83 | 0.61 | 0.72 |
| stages_GSDV | 232 | 0.7368 | 0.5371 | 0.5643 | 0.75 | 0.08 | 0.83 | 0.47 | 0.56 |
| dcsm | 255 | 0.7329 | 0.5575 | 0.5947 | 0.82 | 0.02 | 0.73 | 0.77 | 0.45 |
| shhs_visit2 | 2651 | 0.7301 | 0.5995 | 0.6097 | 0.80 | 0.11 | 0.77 | 0.71 | 0.60 |
| shhs_visit1 | 5793 | 0.7267 | 0.5957 | 0.6001 | 0.80 | 0.10 | 0.77 | 0.69 | 0.62 |
| stages_GSLH | 45 | 0.7178 | 0.5317 | 0.5367 | 0.79 | 0.13 | 0.80 | 0.57 | 0.37 |
| stages_MSMI | 63 | 0.7121 | 0.5953 | 0.5608 | 0.75 | 0.15 | 0.79 | 0.64 | 0.64 |
| stages_GSSW | 105 | 0.7096 | 0.5009 | 0.5234 | 0.72 | 0.07 | 0.81 | 0.36 | 0.54 |
| stages_GSSA | 26 | 0.6989 | 0.4432 | 0.4483 | 0.64 | 0.01 | 0.81 | 0.30 | 0.46 |
| stages_GSBB | 30 | 0.6912 | 0.5546 | 0.5269 | 0.81 | 0.16 | 0.77 | 0.59 | 0.45 |
| stages_MSQW | 153 | 0.6813 | 0.5477 | 0.5151 | 0.77 | 0.23 | 0.79 | 0.45 | 0.51 |
| stages_STLK | 158 | 0.6639 | 0.4954 | 0.4560 | 0.67 | 0.05 | 0.76 | 0.43 | 0.56 |
| hmc | 151 | 0.6634 | 0.6088 | 0.5473 | 0.72 | 0.25 | 0.70 | 0.74 | 0.63 |
| hpap | 247 | 0.6595 | 0.5774 | 0.5192 | 0.71 | 0.17 | 0.72 | 0.69 | 0.59 |
| mesa | 2056 | 0.5748 | 0.4225 | 0.3371 | 0.55 | 0.02 | 0.67 | 0.42 | 0.46 |
| stages_STNF | 460 | 0.5484 | 0.4682 | 0.3925 | 0.63 | 0.00 | 0.57 | 0.67 | 0.47 |
| stages_MSNF | 38 | 0.5108 | 0.2886 | 0.1714 | 0.45 | 0.02 | 0.65 | 0.26 | 0.06 |
| stages_MSTH | 31 | 0.4942 | 0.1529 | -0.0035 | 0.02 | 0.02 | 0.67 | 0.03 | 0.03 |
| stages_MSTR | 285 | 0.4938 | 0.2544 | 0.1110 | 0.30 | 0.01 | 0.64 | 0.25 | 0.08 |
| stages_BOGN | 85 | 0.4578 | 0.1892 | 0.0419 | 0.04 | 0.00 | 0.62 | 0.27 | 0.01 |

## Model Details

- **Architecture**: TsinalisCNN (Tsinalis et al. 2016) — 2-layer CNN on concatenated 5-epoch signal
- **Training data**: Sleep-EDF (153 subjects, single EEG channel)
- **Pipeline**: `identity` (Sleep-EDF) / `raw` (other datasets, resample to 100 Hz)
- **Sequence length**: L=5 epochs
- **Embedding dim**: 500

## 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/ |

## Citations

```bibtex
@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{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},
}
```