Optimization of End-to-End Convolutional Neural Networks for Analysis of Out-of-Hospital Cardiac Arrest Rhythms during Cardiopulmonary Resuscitation

Optimization of End-to-End Convolutional Neural Networks for Analysis of Out-of-Hospital Cardiac Arrest Rhythms during Cardiopulmonary Resuscitation

High performance of the shock advisory analysis of the electrocardiogram (ECG) during cardiopulmonary resuscitation (CPR) in out-of-hospital cardiac arrest (OHCA) is important for better management of the resuscitation protocol. It should provide fewer interruptions of chest compressions (CC) for no...

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Bibliographic Details
Main Authors: Irena Jekova, Vessela Krasteva
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Sensors
Subjects:
deep learning
deep neural network (DNN)
electrocardiogram (ECG)
cardiopulmonary resuscitation (CPR)
chest compressions
ventricular fibrillation (VF)
Online Access:https://www.mdpi.com/1424-8220/21/12/4105

Internet

https://www.mdpi.com/1424-8220/21/12/4105

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