Atrial Fibrillation Classification Using Deep Convolution Networks

Novotna, Petra

Atrial Fibrillation Classification Using Deep Convolution Networks

but.event.date	23.04.2020	cs
but.event.title	Student EEICT 2020	cs
dc.contributor.author	Novotna, Petra
dc.date.accessioned	2021-07-15T11:17:22Z
dc.date.available	2021-07-15T11:17:22Z
dc.date.issued	2020	cs
dc.description.abstract	We propose the usage of three deep convolutional neural networks architectures for classification of a single lead electrocardiogram (ECG) recordings and evaluate them on the atrial fibrillation (AFIB) classification, for which data set was provided by the Department of Biomedical Engineering, BUT. The compared networks are based on ResNet, VGG net and AlexNet. Single lead signals are transformed into the form of spectrogram. AFIB data was augmented for the purpose of similar size of both respected classes and for successful classification. The most successful architecture, based on AlexNet, was found to perform obtaining an accuracy of 92 % and F1 score of 56 % on the hidden testing set.	en
dc.format	text	cs
dc.format.extent	345-349	cs
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Proceedings I of the 26st Conference STUDENT EEICT 2020: General papers. s. 345-349. ISBN 978-80-214-5867-3	cs
dc.identifier.isbn	978-80-214-5867-3
dc.identifier.uri	http://hdl.handle.net/11012/200593
dc.language.iso	en	cs
dc.publisher	Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií	cs
dc.relation.ispartof	Proceedings I of the 26st Conference STUDENT EEICT 2020: General papers	en
dc.relation.uri	https://conf.feec.vutbr.cz/eeict/EEICT2020	cs
dc.rights	© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií	cs
dc.rights.access	openAccess	en
dc.subject	ECG	en
dc.subject	atrial fibrillation	en
dc.subject	signal processing classification	en
dc.subject	deep learning	en
dc.subject	neural networks	en
dc.subject	convolution	en
dc.subject	resnet	en
dc.subject	alexnet	en
dc.subject	vgg	en
dc.title	Atrial Fibrillation Classification Using Deep Convolution Networks	en
dc.type.driver	conferenceObject	en
dc.type.status	Peer-reviewed	en
dc.type.version	publishedVersion	en
eprints.affiliatedInstitution.department	Fakulta elektrotechniky a komunikačních technologií	cs

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