Automatic Human Sleep Stage Scoring Using Deep Neural Networks

The classification of sleep stages is the first and an important step in the quantitative analysis of polysomnographic recordings. Sleep stage scoring relies heavily on visual pattern recognition by a human expert and is time consuming and subjective. Thus, there is a need for automatic classificati...

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Bibliographic Details
Main Authors: Alexander Malafeev, Dmitry Laptev, Stefan Bauer, Ximena Omlin, Aleksandra Wierzbicka, Adam Wichniak, Wojciech Jernajczyk, Robert Riener, Joachim Buhmann, Peter Achermann
Format: Artigo
Language:Inglês
Published: Frontiers Media S.A. 2018-11-01
Series:Frontiers in Neuroscience
Subjects:
deep learning
sleep
EEG
automatic scoring
random forest
artificial neural networks
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2018.00781/full
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