Intra- and inter-epoch temporal context network (IITNet) using sub-epoch features for automatic sleep scoring on raw single-channel EEG

Published in

Biomedical Signal Processing and Control(2020)

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TL;DR

The results support that considering the latest two-minute raw single-channel EEG can be a reasonable choice for sleep scoring via deep neural networks with efficiency and reliability and that introducing intra-epoch temporal context learning with a deep residual network contributes to the improvement in the overall performance.

Authors

Seunghyeok Back

3 papers

Kyoobin Lee

3 papers

H. Seo

1 papers

Seongju Lee

1 papers

Deokhwan Park

1 papers

Tae Kim

1 papers

References57 items

An Australasian Commentary on the AASM Manual for the Scoring of Sleep and Associated Events

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

Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification

A convolutional neural network for sleep stage scoring from raw single-channel EEG

HyCLASSS: A Hybrid Classifier for Automatic Sleep Stage Scoring

Intra- and inter-epoch temporal context network (IITNet) using sub-epoch features for automatic sleep scoring on raw single-channel EEG

Published in

Biomedical Signal Processing and Control(2020)

External Links:

Generate Graph DownloadPDF

TL;DR

Authors

Seunghyeok Back

3 papers

Kyoobin Lee

3 papers

H. Seo

1 papers

Seongju Lee

1 papers

Deokhwan Park

1 papers

Tae Kim

1 papers

References57 items

An Australasian Commentary on the AASM Manual for the Scoring of Sleep and Associated Events

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

Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification

A convolutional neural network for sleep stage scoring from raw single-channel EEG

HyCLASSS: A Hybrid Classifier for Automatic Sleep Stage Scoring

Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification

Automatic differentiation in PyTorch

The use of neural networks in the analysis of sleep stages and the diagnosis of narcolepsy

Deep convolutional neural networks for interpretable analysis of EEG sleep stage scoring

SLEEPNET: Automated Sleep Staging System via Deep Learning

A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series

DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG

Automatic sleep stages classification based on iterative filtering of electroencephalogram signals

Mixed Neural Network Approach for Temporal Sleep Stage Classification

A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features

Sleep Stage Classification Using EEG Signal Analysis: A Comprehensive Survey and New Investigation

Hierarchical Question-Image Co-Attention for Visual Question Answering

Identity Mappings in Deep Residual Networks

Computer-aided sleep staging using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and bootstrap aggregating

Deep Residual Learning for Image Recognition

Convolutional Neural Network for Multi-Category Rapid Serial Visual Presentation BCI

Automatic Sleep Stage Scoring Using Time-Frequency Analysis and Stacked Sparse Autoencoders

Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines

An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition

Withstanding the obstructive sleep apnea syndrome at the expense of arousal instability, altered cerebral autoregulation and neurocognitive decline.

Adam: A Method for Stochastic Optimization

Montreal Archive of Sleep Studies: an open‐access resource for instrument benchmarking and exploratory research

Analysis and Classification of Sleep Stages Based on Difference Visibility Graphs From a Single-Channel EEG Signal

Scoring accuracy of automated sleep staging from a bipolar electroocular recording compared to manual scoring by multiple raters.

Speech recognition with deep recurrent neural networks

Automatic sleep stage recurrent neural classifier using energy features of EEG signals

The American Academy of Sleep Medicine Inter-scorer Reliability Program: Sleep Stage Scoring

An ensemble system for automatic sleep stage classification using single channel EEG signal

Automated sleep stage identification system based on time-frequency analysis of a single EEG channel and random forest classifier

Automatic Stage Scoring of Single-Channel Sleep EEG by Using Multiscale Entropy and Autoregressive Models

Modeling electroencephalography waveforms with semi-supervised deep belief nets: fast classification and anomaly measurement

Sleep and circadian rhythm disruption in psychiatric and neurodegenerative disease

Classification of patterns of EEG synchronization for seizure prediction

A systematic analysis of performance measures for classification tasks

Automatic analysis of single-channel sleep EEG: validation in healthy individuals.

Recipes for the linear analysis of EEG

2005 Special Issue: Framewise phoneme classification with bidirectional LSTM and other neural network architectures

Learning Precise Timing with LSTM Recurrent Networks

Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG

The Sleep Heart Health Study: design, rationale, and methods.

Long Short-Term Memory

Bidirectional recurrent neural networks

A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects: A. Rechtschaffen and A. Kales (Editors). (Public Health Service, U.S. Government Printing Office, Washington, D.C., 1968, 58 p., $4.00)

TL;DR

Authors

References57 items

An Australasian Commentary on the AASM Manual for the Scoring of Sleep and Associated Events

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

Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification

A convolutional neural network for sleep stage scoring from raw single-channel EEG

HyCLASSS: A Hybrid Classifier for Automatic Sleep Stage Scoring

TL;DR

Authors

References57 items

An Australasian Commentary on the AASM Manual for the Scoring of Sleep and Associated Events

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

Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification

A convolutional neural network for sleep stage scoring from raw single-channel EEG

HyCLASSS: A Hybrid Classifier for Automatic Sleep Stage Scoring

Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification

Automatic differentiation in PyTorch

The use of neural networks in the analysis of sleep stages and the diagnosis of narcolepsy

Deep convolutional neural networks for interpretable analysis of EEG sleep stage scoring

SLEEPNET: Automated Sleep Staging System via Deep Learning

A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series

Mask R-CNN

DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG

Automatic sleep stages classification based on iterative filtering of electroencephalogram signals

Mixed Neural Network Approach for Temporal Sleep Stage Classification

A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features

Sleep Stage Classification Using EEG Signal Analysis: A Comprehensive Survey and New Investigation

Hierarchical Question-Image Co-Attention for Visual Question Answering

Identity Mappings in Deep Residual Networks

Computer-aided sleep staging using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and bootstrap aggregating

Deep Residual Learning for Image Recognition

Convolutional Neural Network for Multi-Category Rapid Serial Visual Presentation BCI

Automatic Sleep Stage Scoring Using Time-Frequency Analysis and Stacked Sparse Autoencoders

Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines

An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition

Withstanding the obstructive sleep apnea syndrome at the expense of arousal instability, altered cerebral autoregulation and neurocognitive decline.

Adam: A Method for Stochastic Optimization

Montreal Archive of Sleep Studies: an open‐access resource for instrument benchmarking and exploratory research

Analysis and Classification of Sleep Stages Based on Difference Visibility Graphs From a Single-Channel EEG Signal

Scoring accuracy of automated sleep staging from a bipolar electroocular recording compared to manual scoring by multiple raters.

Speech recognition with deep recurrent neural networks

Automatic sleep stage recurrent neural classifier using energy features of EEG signals

Automatic sleep stage recurrent neural classifier using energy features of EEG signals

The American Academy of Sleep Medicine Inter-scorer Reliability Program: Sleep Stage Scoring

An ensemble system for automatic sleep stage classification using single channel EEG signal

Automated sleep stage identification system based on time-frequency analysis of a single EEG channel and random forest classifier

Automatic Stage Scoring of Single-Channel Sleep EEG by Using Multiscale Entropy and Autoregressive Models

Modeling electroencephalography waveforms with semi-supervised deep belief nets: fast classification and anomaly measurement

Sleep and circadian rhythm disruption in psychiatric and neurodegenerative disease

Classification of patterns of EEG synchronization for seizure prediction

A systematic analysis of performance measures for classification tasks

Automatic analysis of single-channel sleep EEG: validation in healthy individuals.

Recipes for the linear analysis of EEG

2005 Special Issue: Framewise phoneme classification with bidirectional LSTM and other neural network architectures

Learning Precise Timing with LSTM Recurrent Networks

Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG

The Sleep Heart Health Study: design, rationale, and methods.

Long Short-Term Memory

Bidirectional recurrent neural networks

A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects: A. Rechtschaffen and A. Kales (Editors). (Public Health Service, U.S. Government Printing Office, Washington, D.C., 1968, 58 p., $4.00)

A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects.

A Coefficient of Agreement for Nominal Scales

Sleep Stage Classification Using Unsupervised Feature Learning

The American Academy of Sleep Medicine (AASM) Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications

Physionet: components of a new research resource for complex physiologic signals

On the effect of data set size on bias and variance in classification learning

“Sleep data – national sleep research resource – nsrr,”

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