Enhancing the accuracy of shock advisory algorithms in automated external defibrillators during ongoing cardiopulmonary resuscitation using a deep convolutional Encoder-Decoder filtering model

•This is a new filtering technique for AEDs to suppress CPR artifacts from ECG signal.•We demonstrated an application of a deep convolutional encoder-decoder method in AEDs.•Results indicate continuous and accurate AED rhythm analysis without stoppage of CPR.•The observed result of the proposed mode...

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Veröffentlicht in:	Expert systems with applications Jg. 203; S. 117499
Hauptverfasser:	Hajeb-M, Shirin, Cascella, Alicia, Valentine, Matt, Chon, K.H.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.10.2022
Schlagworte:	Autoencoder denoising Automated external defibrillation (AED) Cardiopulmonary resuscitation (CPR) Deep convolutional neural network encoder-decoder (CNNED) OHCA Autoencoder denoising OHCA Cardiopulmonary resuscitation (CPR) Deep convolutional neural network encoder-decoder (CNNED) Automated external defibrillation (AED)
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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