Preliminary Results of Ocular Artefacts Identification in EEC Series by Neural Network

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dc.contributor.authorKofronova, M.
dc.coverage.issue2cs
dc.coverage.volume5cs
dc.date.accessioned2016-05-06T10:22:59Z
dc.date.available2016-05-06T10:22:59Z
dc.date.issued1996-06cs
dc.description.abstractThe human electroencephalogram (EEG), is record of the electrical activity of the brain and contains useful diagnostic information on a variety of neurological disorders. Normal EEG signal are usually registered from electrodes placed on the scalp, and are often very small in amplitude, of 20 µV. The EEG, like all biomedical signals, is very susceptible to a variety of large signal contamination or artefacts (signals of other than brain activity) which reduce its clinical usefulness. For example, blinking or moving eyes produces large electrical potentials around the eyes called the electrooculogram (EOG). The EOG spreads across the scalp to contaminate the EEG, when it is referred to as an ocular artefact (OA). This paper includes method of identification portion of the EEG record where ocular artefact appears and classification its type by neural network.en
dc.formattextcs
dc.format.extent22-24cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 1996, vol. 5, č. 2, s. 22-24. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/58414
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/1996/96_02_06.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectelectroencephalogramen
dc.subjectEEGen
dc.subjectelectrooculogramen
dc.subjectEOGen
dc.subjectocular artefakten
dc.subjectneural networken
dc.subjectbackpropagationen
dc.subjectparametric backpropagationen
dc.titlePreliminary Results of Ocular Artefacts Identification in EEC Series by Neural Networken
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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