AIMC Topic: Sleep Stages
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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...
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...
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...
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...
Automatic Sleep Staging Employing Convolutional Neural Networks and Cortical Connectivity Images.
IEEE transactions on neural networks and learning systems
Mar 15, 2019
Understanding of the neuroscientific sleep mechanisms is associated with mental/cognitive and physical well-being and pathological conditions. A prerequisite for further analysis is the identification of the sleep macroarchitecture through manual sle...
Sleep staging from single-channel EEG with multi-scale feature and contextual information.
Sleep & breathing = Schlaf & Atmung
Mar 12, 2019
PURPOSE: Portable sleep monitoring devices with less-attached sensors and high-accuracy sleep staging methods can expedite sleep disorder diagnosis. The aim of this study was to propose a single-channel EEG sleep staging model, SleepStageNet, which e...
A deep learning approach for real-time detection of sleep spindles.
Journal of neural engineering
Feb 21, 2019
OBJECTIVE: Sleep spindles have been implicated in memory consolidation and synaptic plasticity during NREM sleep. Detection accuracy and latency in automatic spindle detection are critical for real-time applications.
A Deep Learning Model for Automated Sleep Stages Classification Using PSG Signals.
International journal of environmental research and public health
Feb 19, 2019
Sleep disorder is a symptom of many neurological diseases that may significantly affect the quality of daily life. Traditional methods are time-consuming and involve the manual scoring of polysomnogram (PSG) signals obtained in a laboratory environme...
SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 31, 2019
Automatic sleep staging has been often treated as a simple classification problem that aims at determining the label of individual target polysomnography epochs one at a time. In this paper, we tackle the task as a sequence-to-sequence classification...
Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals.
Computers in biology and medicine
Jan 19, 2019
Automated evaluation of a subject's neurocognitive performance (NCP) is a relevant topic in neurological and clinical studies. NCP represents the mental/cognitive human capacity in performing a specific task. It is difficult to develop the study prot...
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