Modeling of electrocardiogram signals using predefined signature and envelope vector sets

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dc.authorid0000-0002-7008-4778
dc.authorid0000-0002-4597-0954
dc.authorid0000-0003-1562-5524
dc.contributor.authorGürkan, Hakanen_US
dc.contributor.authorGüz, Ümiten_US
dc.contributor.authorYarman, Bekir Sıddık Binboğaen_US
dc.date.accessioned2015-01-15T23:00:50Z
dc.date.available2015-01-15T23:00:50Z
dc.date.issued2007
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.description.abstractA novel method is proposed to model ECG signals by means of "predefined signature and envelope vector sets (PSEVS)." On a frame basis, an ECG signal is reconstructed by multiplying three model parameters, namely, predefined signature vector (PSV)(R)," "predefined envelope vector (PEV)(K)," and frame-scaling coefficient (FSC). All the PSVs and PEVs are labeled and stored in their respective sets to describe the signal in the reconstruction process. In this case, an ECG signal frame is modeled by means of the members of these sets labeled with indices R and K and the frame-scaling coefficient, in the least mean square sense. The proposed method is assessed through the use of percentage root-mean-square difference (PRD) and visual inspection measures. Assessment results reveal that the proposed method provides significant data compression ratio (CR) with low-level PRD values while preserving diagnostic information. This fact significantly reduces the bandwidth of communication in telediagnosis operations. Copyright (c) 2007 Hakan Gurkan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationGürkan, H., Güz, Ü. & Yarman, B. S. B. (2007). Modeling of electrocardiogram signals using predefined signature and envelope vector sets. Eurasip Journal on Advances in Signal Processing, 2007, 1-12. doi:10.1155/2007/12071en_US
dc.identifier.doi10.1155/2007/12071
dc.identifier.endpage12
dc.identifier.issn1110-8657
dc.identifier.issn1687-6180
dc.identifier.scopus2-s2.0-33947102039
dc.identifier.scopusqualityQ2
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/11729/270
dc.identifier.urihttp://dx.doi.org/10.1155/2007/12071
dc.identifier.volume2007
dc.identifier.wosWOS:000247954200001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorGüz, Ümiten_US
dc.institutionauthorGürkan, Hakanen_US
dc.institutionauthorid0000-0002-7008-4778
dc.institutionauthorid0000-0002-4597-0954
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherHindawi Publishing Corporationen_US
dc.relation.ispartofEURASIP Journal on Advances in Signal Processingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectECG compressionen_US
dc.subjectQuantizationen_US
dc.subjectCodevectorsen_US
dc.subjectAlgorithmen_US
dc.subjectElectrocardiographyen_US
dc.subjectData compressionen_US
dc.subjectSignal compressionen_US
dc.subjectLeast squares approximationsen_US
dc.subjectMathematical modelsen_US
dc.subjectMean square erroren_US
dc.subjectParameter estimationen_US
dc.subjectSignal reconstructionen_US
dc.subjectElectrocardiogram signalsen_US
dc.subjectEnvelope vector setsen_US
dc.subjectFrame scaling coefficient (FSC)en_US
dc.subjectModel parametersen_US
dc.subjectSignal analysisen_US
dc.titleModeling of electrocardiogram signals using predefined signature and envelope vector setsen_US
dc.typeArticleen_US
dspace.entity.typePublication

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