Uncovering the structure of clinical EEG signals with self-supervised learning
paper
published
neuroscience
EEG
deep learning
self supervised
Self-supervised learning with EEG can parse sleep stages and other clinical details
Summary
This Twitter thread summarizes the work and walks you through the main findings.
;document.getElementById("tweet-11701").innerHTML = tweet["html"];Demonstration
You can find example PyTorch code at the Braindecode website.
Citation
@article{banville2021uncovering,
title={Uncovering the structure of clinical EEG signals with self-supervised learning},
author={Banville, Hubert and Chehab, Omar and Hyv{\"a}rinen, Aapo and Engemann, Denis-Alexander and Gramfort, Alexandre},
journal={Journal of Neural Engineering},
volume={18},
number={4},
pages={046020},
year={2021},
publisher={IOP Publishing}
}