DOSED: A deep learning approach to detect multiple sleep micro-events in EEG signal

Published in

Journal of Neuroscience Methods(2018)

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TL;DR

A novel deep learning architecture called Dreem One Shot Event Detector (DOSED) is proposed, inspired by object detectors developed for computer vision such as YOLO and SSD, which predicts locations, durations and types of events in EEG time series.

Authors

Alexandre Gramfort

4 papers

Valentin Thorey

3 papers

E. Mignot

2 papers

Stanislas Chambon

1 papers

P. Arnal

1 papers

References65 items

SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging

Sleep spindle detection using multivariate Gaussian mixture models

A Deep Learning Architecture to Detect Events in EEG Signals During Sleep

Multichannel Sleep Stage Classification and Transfer Learning using Convolutional Neural Networks

Automatic Sleep Stage Classification Using Single-Channel EEG: Learning Sequential Features with Attention-Based Recurrent Neural Networks

DOSED: A deep learning approach to detect multiple sleep micro-events in EEG signal

Published in

Journal of Neuroscience Methods(2018)

External Links:

Generate Graph DownloadPDF

TL;DR

Authors

Alexandre Gramfort

4 papers

Valentin Thorey

3 papers

E. Mignot

2 papers

Stanislas Chambon

1 papers

P. Arnal

1 papers

References65 items

SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging

Sleep spindle detection using multivariate Gaussian mixture models

A Deep Learning Architecture to Detect Events in EEG Signals During Sleep

Multichannel Sleep Stage Classification and Transfer Learning using Convolutional Neural Networks

Automatic Sleep Stage Classification Using Single-Channel EEG: Learning Sequential Features with Attention-Based Recurrent Neural Networks

Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms

Domain adaptation with optimal transport improves EEG sleep stage classifiers

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Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy

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Field of Study

EngineeringComputer ScienceMathematicsMedicine

Journal Information

Name

Journal of Neuroscience Methods

Page

1-16

Volume

288

Venue Information

Name

Journal of Neuroscience Methods

Type

journal

URL

https://www.journals.elsevier.com/journal-of-neuroscience-methods/

Alternate Names

J Neurosci Method