AIMC Topic: Sleep Stages

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Sleep stage classification from heart-rate variability using long short-term memory neural networks.

Scientific reports Oct 2, 2019
Automated sleep stage classification using heart rate variability (HRV) may provide an ergonomic and low-cost alternative to gold standard polysomnography, creating possibilities for unobtrusive home-based sleep monitoring. Current methods however ar...
Humans Neural Networks, Computer Female Middle Aged Models, Neurological Heart Rate Sleep Stages Aged Adult Male
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Orthogonal convolutional neural networks for automatic sleep stage classification based on single-channel EEG.

Computer methods and programs in biomedicine Sep 27, 2019
BACKGROUND AND OBJECTIVE: In recent years, several automatic sleep stage classification methods based on convolutional neural networks (CNN) by learning hierarchical feature representation automatically from raw EEG data have been proposed. However, ...
Humans Sleep Stages Calibration Polysomnography Sleep Wake Disorders Male Databases, Factual Time Factors Sleep Apnea, Obstructive Reproducibility of Results Electrocardiography Neural Networks, Computer Sleep Adult Electroencephalography Sensitivity and Specificity Machine Learning Signal Processing, Computer-Assisted Algorithms
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A Hierarchical Neural Network for Sleep Stage Classification Based on Comprehensive Feature Learning and Multi-Flow Sequence Learning.

IEEE journal of biomedical and health informatics Aug 27, 2019
Automatic sleep staging methods usually extract hand-crafted features or network trained features from signals recorded by polysomnography (PSG), and then estimate the stages by various classifiers. In this study, we propose a classification approach...
Female Young Adult Adult Male Humans Neural Networks, Computer Machine Learning Polysomnography Sleep Stages Electrodiagnosis Middle Aged Adolescent Signal Processing, Computer-Assisted
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Automated sleep scoring: A review of the latest approaches.

Sleep medicine reviews Aug 9, 2019
Clinical sleep scoring involves a tedious visual review of overnight polysomnograms by a human expert, according to official standards. It could appear then a suitable task for modern artificial intelligence algorithms. Indeed, machine learning algor...
Machine Learning Data Analysis Algorithms Sleep Wake Disorders Sleep Stages Diagnosis, Computer-Assisted Polysomnography Humans
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An automatic single-channel EEG-based sleep stage scoring method based on hidden Markov Model.

Journal of neuroscience methods Jun 19, 2019
OBJECTIVE: Sleep stage scoring is essential for diagnosing sleep disorders. Visual scoring of sleep stages is very time-consuming and prone to human errors. In this work, we introduce an efficient approach to improve the accuracy of sleep stage scori...
Sleep Stages Young Adult Adult Humans Male Female Support Vector Machine Signal Processing, Computer-Assisted Electroencephalography Markov Chains
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Deep convolutional neural network for classification of sleep stages from single-channel EEG signals.

Journal of neuroscience methods Jun 12, 2019
Using a smart method for automatic diagnosis in medical applications, such as sleep stage classification is considered as one of the important challenges of the last few years which can replace the time-consuming process of visual inspection done by ...
Electroencephalography Signal Processing, Computer-Assisted Sleep Stages Humans Deep Learning
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Sleep stage classification using covariance features of multi-channel physiological signals on Riemannian manifolds.

Computer methods and programs in biomedicine Jun 10, 2019
BACKGROUND AND OBJECTIVE: The recognition of many sleep related pathologies highly relies on an accurate classification of sleep stages. Clinically, sleep stages are usually labelled by sleep experts through visually inspecting the whole-night polyso...
Machine Learning Algorithms Databases, Factual Data Interpretation, Statistical Electroencephalography Computer Simulation Reproducibility of Results Electrooculography Sleep Stages Humans Signal Processing, Computer-Assisted Sleep Polysomnography
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SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach.

PloS one May 7, 2019
Electroencephalogram (EEG) is a common base signal used to monitor brain activities and diagnose sleep disorders. Manual sleep stage scoring is a time-consuming task for sleep experts and is limited by inter-rater reliability. In this paper, we propo...
Sleep Stages Electroencephalography Humans Signal Processing, Computer-Assisted Deep Learning Sleep Wake Disorders Models, Neurological
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A review of automated sleep stage scoring based on physiological signals for the new millennia.

Computer methods and programs in biomedicine May 2, 2019
BACKGROUND AND OBJECTIVE: Sleep is an important part of our life. That importance is highlighted by the multitude of health problems which result from sleep disorders. Detecting these sleep disorders requires an accurate interpretation of physiologic...
Polysomnography Electrooculography Sleep Stages Heart Rate Electrocardiography Medical Informatics Humans Electroencephalography Normal Distribution Algorithms Signal Processing, Computer-Assisted Deep Learning Internet
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DOSED: A deep learning approach to detect multiple sleep micro-events in EEG signal.

Journal of neuroscience methods Apr 1, 2019
BACKGROUND: Electroencephalography (EEG) monitors brain activity during sleep and is used to identify sleep disorders. In sleep medicine, clinicians interpret raw EEG signals in so-called sleep stages, which are assigned by experts to every 30s windo...
Sleep Polysomnography Humans Deep Learning Arousal Female Electroencephalography Brain Sleep Stages Young Adult Signal Processing, Computer-Assisted Adult Male
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