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dc.contributor.authorMartinek, Radek
dc.contributor.authorLádrová, Martina
dc.contributor.authorŠidiková, Michaela
dc.contributor.authorJaroš, René
dc.contributor.authorBehbehani, Khosrow
dc.contributor.authorKahánková, Radana
dc.contributor.authorKawala-Sterniuk, Aleksandra
dc.date.accessioned2022-04-22T11:48:41Z
dc.date.available2022-04-22T11:48:41Z
dc.date.issued2021
dc.identifier.citationSensors. 2021, vol. 21, issue 15, art. no. 5186.cs
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/10084/146072
dc.description.abstractAdvanced signal processing methods are one of the fastest developing scientific and technical areas of biomedical engineering with increasing usage in current clinical practice. This paper presents an extensive literature review of the methods for the digital signal processing of cardiac bioelectrical signals that are commonly applied in today's clinical practice. This work covers the definition of bioelectrical signals. It also covers to the extreme extent of classical and advanced approaches to the alleviation of noise contamination such as digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation and wavelet transform.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesSensorscs
dc.relation.urihttps://doi.org/10.3390/s21155186cs
dc.rights© 2021 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.subjectbiomedical signalscs
dc.subjectcardiac signalscs
dc.subjectelectrocardiographycs
dc.subjectvectorcardiographycs
dc.subjectfetal electrocardiographycs
dc.titleAdvanced bioelectrical signal processing methods: Past, present and future approach - Part I: Cardiac signalscs
dc.typearticlecs
dc.identifier.doi10.3390/s21155186
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume21cs
dc.description.issue15cs
dc.description.firstpageart. no. 5186cs
dc.identifier.wos000682230600001


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© 2021 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 © 2021 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.