Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram

•Deep learning approaches were designed to automatically detect sleep apnea (SA) from an electrocardiogram signal.•Six deep learning approaches were designed and implemented including DNN, 1D CNN, 2D CNN, RNN, long short-term memory, and gated-recurrent unit models.•The 1D CNN and GRU models were th...

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Veröffentlicht in:	Computer methods and programs in biomedicine 2019-10, Vol.180, p.105001-105001, Article 105001
Hauptverfasser:	Erdenebayar, Urtnasan, Kim, Yoon Ji, Park, Jong-Uk, Joo, Eun Yeon, Lee, Kyoung-Joung
Format:	Artikel
Sprache:	eng
Schlagworte:	Automation Convolutional neural network Databases, Factual Deep Learning Electrocardiography Gated-recurrent unit Humans Long short-term memory Recurrent neural network Sleep apnea Sleep Apnea Syndromes - diagnosis
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