AIMC Topic: Sleep Stages
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A Residual Based Attention Model for EEG Based Sleep Staging.
IEEE journal of biomedical and health informatics
Mar 3, 2020
Sleep staging is to score the sleep state of a subject into different sleep stages such as Wake and Rapid Eye Movement (REM). It plays an indispensable role in the diagnosis and treatment of sleep disorders. As manual sleep staging through well-train...
A Deep Learning Approach for Automated Sleep-Wake Scoring in Pre-Clinical Animal Models.
Journal of neuroscience methods
Mar 2, 2020
BACKGROUND: Experimental investigation of sleep-wake dynamics in animals is an important part of pharmaceutical development. Typically, it involves recording of electroencephalogram, electromyogram, locomotor activity, and electrooculogram. Visual id...
A-phase classification using convolutional neural networks.
Medical & biological engineering & computing
Mar 2, 2020
A series of short events, called A-phases, can be observed in the human electroencephalogram (EEG) during Non-Rapid Eye Movement (NREM) sleep. These events can be classified in three groups (A1, A2, and A3) according to their spectral contents, and a...
Automated multi-model deep neural network for sleep stage scoring with unfiltered clinical data.
Sleep & breathing = Schlaf & Atmung
Jan 14, 2020
PURPOSE: To develop an automated framework for sleep stage scoring from PSG via a deep neural network.
A convolutional neural network outperforming state-of-the-art sleep staging algorithms for both preterm and term infants.
Journal of neural engineering
Jan 14, 2020
OBJECTIVE: To classify sleep states using electroencephalogram (EEG) that reliably works over a wide range of preterm ages, as well as term age.
Accurate Deep Learning-Based Sleep Staging in a Clinical Population With Suspected Obstructive Sleep Apnea.
IEEE journal of biomedical and health informatics
Dec 19, 2019
The identification of sleep stages is essential in the diagnostics of sleep disorders, among which obstructive sleep apnea (OSA) is one of the most prevalent. However, manual scoring of sleep stages is time-consuming, subjective, and costly. To overc...
Revisiting the value of polysomnographic data in insomnia: more than meets the eye.
Sleep medicine
Dec 13, 2019
BACKGROUND: Polysomnography (PSG) is not recommended as a diagnostic tool in insomnia. However, this consensual approach might be tempered in the light of two ongoing transformations in sleep research: big data and artificial intelligence (AI).
A hybrid self-attention deep learning framework for multivariate sleep stage classification.
BMC bioinformatics
Dec 2, 2019
BACKGROUND: Sleep is a complex and dynamic biological process characterized by different sleep patterns. Comprehensive sleep monitoring and analysis using multivariate polysomnography (PSG) records has achieved significant efforts to prevent sleep-re...
MC-SleepNet: Large-scale Sleep Stage Scoring in Mice by Deep Neural Networks.
Scientific reports
Oct 31, 2019
Automated sleep stage scoring for mice is in high demand for sleep research, since manual scoring requires considerable human expertise and efforts. The existing automated scoring methods do not provide the scoring accuracy required for practical use...
A hierarchical sequential neural network with feature fusion for sleep staging based on EOG and RR signals.
Journal of neural engineering
Oct 29, 2019
OBJECTIVE: Currently, the automatic sleep staging methods mainly face two problems: the first problem is that although the algorithms which use electroencephalogram (EEG) signals perform well, acquiring EEG signals is complicated and uncomfortable; t...
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