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dc.contributor.authorJaroš, René
dc.contributor.authorMartinek, Radek
dc.contributor.authorKahánková, Radana
dc.date.accessioned2019-01-04T12:20:12Z
dc.date.available2019-01-04T12:20:12Z
dc.date.issued2018
dc.identifier.citationSensors. 2018, vol. 18, issue 11, art. no. 3648.cs
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/10084/133480
dc.description.abstractFetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.cs
dc.format.extent961441 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesSensorscs
dc.relation.urihttp://doi.org/10.3390/s18113648cs
dc.rights© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectnon-adaptive filteringcs
dc.subjectfetal electrocardiogram extractioncs
dc.subjectfetal monitoringcs
dc.subjectdigital signal processingcs
dc.titleNon-adaptive methods for fetal ECG signal processing: A review and appraisalcs
dc.typearticlecs
dc.identifier.doi10.3390/s18113648
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume18cs
dc.description.issue11cs
dc.description.firstpageart. no. 3648cs
dc.identifier.wos000451598900058


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Zobrazit minimální záznam

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.