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dc.contributor.authorUher, Daniel
dc.date.accessioned2019-03-04T10:05:38Z
dc.date.available2019-03-04T10:05:38Z
dc.date.issued2018cs
dc.identifier.citationProceedings of the 24th Conference STUDENT EEICT 2018. s. 107-109. ISBN 978-80-214-5614-3cs
dc.identifier.isbn978-80-214-5614-3
dc.identifier.urihttp://hdl.handle.net/11012/138183
dc.description.abstractThe idea of an artifact-free brain activity recording has been circling around the scientific world for a few decades. Noise present in brain activity recordings may complicate the process of evaluation and interpretation. For the elimination of such unwanted components, the concept of virtual reference signals is usually used. In this work, the algorithms for reference signal estimation using common average-based method as well as more recent methods based on independent component analysis (ICA) were realized and evaluated on a new set of real clinical data. It was found that the ICA-based algorithms allow obtaining more accurate estimation of the reference signal as compared to the average-based one. Finally, all the methods were implemented into a free installable Python toolbox, which will be publicly available after additional testing on real data.en
dc.formattextcs
dc.format.extent107-109cs
dc.format.mimetypeapplication/pdfen
dc.language.isoczcs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 24th Conference STUDENT EEICT 2018en
dc.relation.urihttp://www.feec.vutbr.cz/EEICT/cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.subjectReference signalsen
dc.subjectreferenceen
dc.subjectintracranial EEGen
dc.subjectICAen
dc.subjectaverageen
dc.subjectcorrelationen
dc.titleReference Signals In Intracranial Eeg: Implementation And Analysisen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
but.event.date26.04.2018cs
but.event.titleStudent EEICT 2018cs
dc.rights.accessopenAccessen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionPublishers's versionen


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