Enhancing the accuracy of shock advisory algorithms in automated external defibrillators during ongoing cardiopulmonary resuscitation using a cascade of CNNEDs

Delivery of continuous cardiopulmonary resuscitation (CPR) plays an important role in the out-of-hospital cardiac arrest (OHCA) survival rate. However, to prevent CPR artifacts being superimposed on ECG morphology data, currently available automated external defibrillators (AEDs) require pauses in C...

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Veröffentlicht in:	Computers in biology and medicine 2024-04, Vol.172, p.108180, Article 108180
Hauptverfasser:	Nejad, Mahdi Pirayesh Shirazi, Kargin, Vadym, Hajeb-M, Shirin, Hicks, David, Valentine, Matt, Chon, K.H.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Arrhythmias, Cardiac - diagnosis Artificial neural networks Automation Cardiac arrest Cardiac arrhythmia Cardiopulmonary resuscitation Cardiopulmonary Resuscitation - methods Classification Contamination Convolutional Neural Network CPR Decision analysis Decision making Defibrillators Defibrillatory shock EKG Electrocardiogram Electrocardiography Electrocardiography - methods Encoder and decoder Encoders-Decoders Fibrillation Heart rate Humans Lifesaving Neural networks Performance evaluation Reference signals Reproducibility of Results Resuscitation Rhythm Segments Shock Signal processing Sudden cardiac arrest Survival Tachycardia Tachycardia, Ventricular Test sets Ventricle Ventricular Fibrillation Ventricular tachycardia
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