SleepFCN: A Fully Convolutional Deep Learning Framework for Sleep Stage Classification Using Single-Channel Electroencephalograms

SleepFCN: A Fully Convolutional Deep Learning Framework for Sleep Stage Classification Using Single-Channel Electroencephalograms

Sleep is a vital process of our daily life as we roughly spend one-third of our lives asleep. In order to evaluate sleep quality and potential sleep disorders, sleep stage classification is a gold standard method. In this paper, we introduce a novel fully convolutional neural network architecture (S...

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Bibliographic Details
Main Authors: Narjes Goshtasbi, Reza Boostani, Saeid Sanei
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
CNN
deep learning
EEG
single-channel
sleep stage classification
Online Access:https://ieeexplore.ieee.org/document/9834934/

Internet

https://ieeexplore.ieee.org/document/9834934/

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