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dc.contributor.authorBeháňová, Andrea
dc.date.accessioned2020-05-07T09:40:26Z
dc.date.available2020-05-07T09:40:26Z
dc.date.issued2017cs
dc.identifier.citationProceedings of the 23st Conference STUDENT EEICT 2017. s. 124-126. ISBN 978-80-214-5496-5cs
dc.identifier.isbn978-80-214-5496-5
dc.identifier.urihttp://hdl.handle.net/11012/187057
dc.description.abstractIn this study, we focus on the estimation of ECG signal quality. It consists of two parts, first includes generating artificial ECG, artificial myopotentials, implementation of Adaptive Wavelet Wiener Filter and continuous calculation of the Signal-to-Noise Ratio (SNR). The second part includes segmentation process, which sorts parts of ECG signal into three categories: suitable for full wave analysis, good for QRS detection and unsuitable for further processing.en
dc.formattextcs
dc.format.extent124-126cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 23st Conference STUDENT EEICT 2017en
dc.relation.urihttp://www.feec.vutbr.cz/EEICT/cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.subjectECG signalen
dc.subjectnoise estimationen
dc.subjectECG qualityen
dc.subjectAdaptive Wavelet Wiener Filteren
dc.subjectECG segmentationen
dc.titleReal-Time Estimation Of ECG Signal Qualityen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
but.event.date27.04.2017cs
but.event.titleStudent EEICT 2017cs
dc.rights.accessopenAccessen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionPublishers's versionen


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