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Proceedings 2018, 2(18), 1174; https://doi.org/10.3390/proceedings2181174

A Convolutional Network for the Classification of Sleep Stages

CITIC, Universidade da Coruña, A Coruña, 15071 Spain
Presented at the XoveTIC Congress, A Coruña, Spain, 27–28 September 2018.
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Published: 14 September 2018
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Abstract

The classification of sleep stages is a crucial task in the context of sleep medicine. It involves the analysis of multiple signals thus being tedious and complex. Even for a trained physician scoring a whole night sleep study can take several hours. Most of the automatic methods trying to solve this problem use human engineered features biased for a specific dataset. In this work we use deep learning to avoid human bias. We propose an ensemble of 5 convolutional networks achieving a kappa index of 0.83 when classifying 500 sleep studies.
Keywords: sleep staging; convolutional neural network; classification sleep staging; convolutional neural network; classification
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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MDPI and ACS Style

Fernández-Varela, I.; Hernández-Pereira, E.; Moret-Bonillo, V. A Convolutional Network for the Classification of Sleep Stages. Proceedings 2018, 2, 1174.

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