The research of sleep staging based on single-lead electrocardiogram and deep neural network

The polysomnogram (PSG) analysis is considered the golden standard for sleep staging under the clinical environment. The electroencephalogram (EEG) signal is the most important signal for classification of sleep stages. However, in-vivo signal recording and analysis of EEG signal presents us with a...

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Veröffentlicht in:	Biomedical engineering letters Jg. 8; H. 1; S. 87 - 93
Hauptverfasser:	Wei, Ran, Zhang, Xinghua, Wang, Jinhai, Dang, Xin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Korea The Korean Society of Medical and Biological Engineering 01.02.2018 Springer Nature B.V 대한의용생체공학회
Schlagworte:	Artificial neural networks Biological and Medical Physics Biomedical Engineering and Bioengineering Biomedicine Biophysics Classification EEG EKG Electrocardiography Electroencephalography Engineering Feature extraction Medical and Radiation Physics Model accuracy Model testing Neural networks NREM sleep Original Original Article Recording REM sleep Sleep Sleep and wakefulness 의공학 Stacked autoencoder (SAE) Sleep stage Electrocardiogram (ECG) Deep neural network (DNN)
ISSN:	2093-9868, 2093-985X, 2093-985X
Online-Zugang:	Volltext
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