Single-Feature Method for Fast Atrial Fibrillation Detection in ECG Signals

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dc.contributor.authorŠaclová, Luciecs
dc.contributor.authorNěmcová, Andreacs
dc.contributor.authorSmíšek, Radovancs
dc.contributor.authorSmital, Lukášcs
dc.contributor.authorVítek, Martincs
dc.coverage.issue1cs
dc.coverage.volume47cs
dc.date.issued2020-12-28cs
dc.description.abstractAtrial fibrillation (AF) is the most common arrhthmia in adults and is associated with higher risk of heart failure or death. Here, we introduce simple and efficient method for automatic AF detection based on symbolic dynamics and Shannon entropy. This method comprises of three parts. Firstly, QRS complex detection is provided, than the raw RR sequence is transformed into a sequence of specific symbols and subsequently into a word sequence and finally, Shannon entropy of the word sequence is calculated. According to the value of Shannon entropy, it is decided, whether AF is present in the current cardiac beat. We achieved sensitivity Se=96.32% and specificity Sp=98.61 on MIT-BIH Atrial Fibrillation database, Se=91.30% and Sp=90.80% on MIT-BIH Arrhythmia database, Se=95.6% and Sp=80.27% for CinC Challenge database 2020. The achieved results of our one-feature method are comparable with other authors of more complicated and computationally expensive methods.en
dc.formattextcs
dc.format.extent1-4cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationComputing in Cardiology. 2020, vol. 47, issue 1, p. 1-4.en
dc.identifier.doi10.22489/CinC.2020.335cs
dc.identifier.issn2325-887Xcs
dc.identifier.orcid0000-0003-1638-4814cs
dc.identifier.orcid0000-0003-1801-7057cs
dc.identifier.orcid0000-0003-0413-3604cs
dc.identifier.orcid0000-0003-1526-4626cs
dc.identifier.orcid0000-0002-8059-1087cs
dc.identifier.other166074cs
dc.identifier.researcheridAAL-7695-2021cs
dc.identifier.researcheridAAH-1590-2021cs
dc.identifier.researcheridF-5329-2017cs
dc.identifier.researcheridH-8505-2014cs
dc.identifier.researcheridD-3351-2014cs
dc.identifier.scopus57188871806cs
dc.identifier.scopus6507784572cs
dc.identifier.scopus57188873046cs
dc.identifier.scopus54960986600cs
dc.identifier.scopus35767287500cs
dc.identifier.urihttp://hdl.handle.net/11012/196703
dc.language.isoencs
dc.publisherIEEEcs
dc.relation.ispartofComputing in Cardiologycs
dc.relation.urihttp://www.cinc.org/archives/2020/pdf/CinC2020-335.pdfcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2325-887X/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectECGen
dc.subjectatrial fibrillationen
dc.subjectphasor transformen
dc.subjectsymbolic dynamicen
dc.titleSingle-Feature Method for Fast Atrial Fibrillation Detection in ECG Signalsen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-166074en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:39:46en
sync.item.modts2025.01.17 16:51:05en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav biomedicínského inženýrstvícs
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