EEG signal compression based on classified 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.accessioned2015-01-15T23:01:19Z
dc.date.available2015-01-15T23:01:19Z
dc.date.issued2009-03
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.description.abstractIn this paper, a novel method to compress electroencephalogram (EEG) signal is proposed. The proposed method is based on the generation process of the classified signature and envelope vector sets (CSEVS), which employs an effective k-means clustering algorithm. It is assumed that both the transmitter and the receiver units have the same CSEVS. In this work, on a frame basis, EEG signals are modeled by multiplying only three factors called as classified signature vector, classified envelope vector, and gain coefficient (GC), respectively. In other words, every frame of an EEG signal is represented by two indices R and K of CSEVS and the GC. EEG signals are reconstructed frame by frame using these numbers in the receiver unit by employing the CSEVS. The proposed method is evaluated by using some evaluation metrics that are commonly used in this area such as root-mean-square error, percentage root-mean-square difference, and measuring with visual inspection. The performance of the proposed method is also compared with the other methods. It is observed that the proposed method achieves high compression ratios with low-level reconstruction error while preserving diagnostic information in the reconstructed EEG signal.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationGürkan, H., Güz, Ü. & Yarman, B. S. B. (2009). EEG signal compression based on classified signature and envelope vector sets. International Journal of Circuit Theory and Applications, 37(2), 351-363. doi:10.1002/cta.548en_US
dc.identifier.doi10.1002/cta.548
dc.identifier.endpage363
dc.identifier.issn0098-9886
dc.identifier.issn1097-007X
dc.identifier.issue2
dc.identifier.scopus2-s2.0-61349157343
dc.identifier.scopusqualityQ2
dc.identifier.startpage351
dc.identifier.urihttps://hdl.handle.net/11729/337
dc.identifier.urihttp://dx.doi.org/10.1002/cta.548
dc.identifier.volume37
dc.identifier.wosWOS:000264012600013
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.indekslendigikaynakConference Proceedings Citation Index – Science (CPCI-S)en_US
dc.institutionauthorGürkan, Hakanen_US
dc.institutionauthorGüz, Ümiten_US
dc.institutionauthorid0000-0002-7008-4778
dc.institutionauthorid0000-0002-4597-0954
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherWileyen_US
dc.relation.ispartofInternational Journal of Circuit Theory and Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEEGen_US
dc.subjectCompressionen_US
dc.subjectModelingen_US
dc.subjectWaveletsen_US
dc.subjectClustering algorithmsen_US
dc.subjectVectorsen_US
dc.subjectVisual communicationen_US
dc.subjectA-framesen_US
dc.subjectDiagnostic informationsen_US
dc.subjectEEG signalsen_US
dc.subjectEvaluation metricsen_US
dc.subjectGain coefficientsen_US
dc.subjectGeneration processen_US
dc.subjectHigh compression ratiosen_US
dc.subjectK-means clustering algorithmsen_US
dc.subjectNovel methodsen_US
dc.subjectPercentage root-mean-square differencesen_US
dc.subjectReconstruction errorsen_US
dc.subjectRoot-mean-square errorsen_US
dc.subjectSignature vectorsen_US
dc.subjectVisual inspectionsen_US
dc.subjectElectroencephalographyen_US
dc.titleEEG signal compression based on classified signature and envelope vector setsen_US
dc.typeArticleen_US
dspace.entity.typePublication

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