Multichannel QRS Morphology Clustering - Data Preprocessing for Ultra-High-Frequency ECG Analysis

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dc.contributor.authorPlešinger, Filipcs
dc.contributor.authorJurčo, Jurajcs
dc.contributor.authorHalámek, Josefcs
dc.contributor.authorLeinveber, Pavelcs
dc.contributor.authorPostránecká, Terezacs
dc.contributor.authorJurák, Pavelcs
dc.date.issued2015-11-06cs
dc.description.abstractUltra-high-frequency ECG (UHF-ECG) in a range of 500–1,000 Hz has been tested as a new information source for analysis of left-ventricle dyssynchrony and other myocardial abnormalities. The power of UHF signals is extremely low, for which reason an averaging technique is used to improve signal-to-noise ratio. Since ventricle dyssynchrony is different for various QRS complex types, the detected QRS complexes must be clustered into morphology groups prior to averaging. Here, we present a fully-automated method for clustering. The first goal of the method is to separate previously detected QRS complexes into different morphology groups. The second goal is to precisely fit the QRS annotation marks to the exact same position against the QRS shape. The method is based on the Pearson correlation and is optimized for parallel processing. In our application with UHF-ECG data the number of detected groups was 3.24 ± 3.41 (mean and standard deviation over 1,030 records). The method can be used in other areas also where the clustering of repetitive signal formations is needed. For validation purposes, the method was tested on the MIT-BIH Arrhythmia and INCART databases from Physionet with results of purity of 98.24% and 99.50%.en
dc.formattextcs
dc.format.extent11-19cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationProceedings of the 3rd International Congress on Cardiovascular Technologies. 2015, p. 11-19.en
dc.identifier.doi10.5220/0005604200110019cs
dc.identifier.isbn978-989-758-160-1cs
dc.identifier.orcid0000-0001-7267-4408cs
dc.identifier.other128354cs
dc.identifier.urihttp://hdl.handle.net/11012/201037
dc.language.isoencs
dc.publisherScience and Technology Publicationscs
dc.relation.ispartofProceedings of the 3rd International Congress on Cardiovascular Technologiescs
dc.relation.urihttps://www.scitepress.org/Link.aspx?doi=10.5220/0005604200110019cs
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/cs
dc.subjectECGen
dc.subjectSAECGen
dc.subjectQRSen
dc.subjectUltra-High-Frequencyen
dc.subjectClusteringen
dc.subjectMulti-threaden
dc.subjectVentricle Dyssynchronyen
dc.titleMultichannel QRS Morphology Clustering - Data Preprocessing for Ultra-High-Frequency ECG Analysisen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-128354en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:39:47en
sync.item.modts2025.01.17 18:47:24en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav biomedicínského inženýrstvícs
thesis.grantorVysoké učení technické v Brně. . Ústav přístrojové techniky AV ČRcs
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