Recurrent Neural Network Based Classification of ECG Signal Features for Obstruction of Sleep Apnea Detection

Published: Jul 1, 2017
Abstract
This paper introduces an OSA detection method based on Recurrent Neural network. At the first step, RR interval (time interval from one R wave to the next R wave) is employed to extract the signals from Apnea- Electrocardiogram (ECG) where all extracted features are then used as an input for the designed deep model. Then an architecture having four recurrent layers and batch normalization layers are designed and trained with the extracted...
Paper Details
Title
Recurrent Neural Network Based Classification of ECG Signal Features for Obstruction of Sleep Apnea Detection
Published Date
Jul 1, 2017
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