Optimal Parameters of Adaptive Segmentation for Epileptic Graphoelements Recognition

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dc.contributor.authorKala, David
dc.contributor.authorKrajca, Vladimir
dc.contributor.authorSchaabova, Hana
dc.contributor.authorLhotska, Lenka
dc.contributor.authorGerla, Vaclav
dc.coverage.issue1cs
dc.coverage.volume26cs
dc.date.accessioned2017-04-18T08:21:46Z
dc.date.available2017-04-18T08:21:46Z
dc.date.issued2017-04cs
dc.description.abstractManual review of EEG records, as it is per¬formed in common medical practice, is very time-consuming. There is an effort to make this analysis easier and faster for neurologists by using systems for automatic EEG graphoelements recognition. Such a system is composed of three steps: (1) segmentation, which is a subject of this article, (2) features extraction and (3) classification. Precision of classification, and thereby the whole recognition, is strongly affected by the quality of preceding segmentation procedure, which depends on the method of segmentation and its parameters. In this paper, Varri’s method for segmentation of real epileptic EEG signals is used. Effect of input parameters on segmentation outcome is discussed and parameters values are proposed to achieve optimal outcome suitable for the following classification and graphoelements recognition. Only the results of segmentation are presented in this paper.en
dc.formattextcs
dc.format.extent323-329cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2017 vol. 26, č. 1, s. 323-329. ISSN 1210-2512cs
dc.identifier.doi10.13164/re.2017.0323en
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/64740
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2017/17_01_0323_0329.pdfcs
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectEEGen
dc.subjectadaptive segmentationen
dc.subjectepilepsyen
dc.subjecttwo connected windows methoden
dc.titleOptimal Parameters of Adaptive Segmentation for Epileptic Graphoelements Recognitionen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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