Representative QRS loop of the VCG record evaluation

dc.contributor.authorKijonka, Jan
dc.contributor.authorVávra, Petr
dc.contributor.authorPenhaker, Marek
dc.contributor.authorKubíček, Jan
dc.date.accessioned2024-09-20T12:31:15Z
dc.date.available2024-09-20T12:31:15Z
dc.date.issued2024
dc.description.abstractIntroduction: This study proposes an algorithm for preprocessing VCG records to obtain a representative QRS loop. Methods: The proposed algorithm uses the following methods: Digital filtering to remove noise from the signal, wavelet-based detection of ECG fiducial points and isoelectric PQ intervals, spatial alignment of QRS loops, QRS time synchronization using root mean square error minimization and ectopic QRS elimination. The representative QRS loop is calculated as the average of all QRS loops in the VCG record. The algorithm is evaluated on 161 VCG records from a database of 58 healthy control subjects, 69 patients with myocardial infarction, and 34 patients with bundle branch block. The morphologic intra-individual beat-to-beat variability rate is calculated for each VCG record. Results and Discussion: The maximum relative deviation is 12.2% for healthy control subjects, 19.3% for patients with myocardial infarction, and 17.2% for patients with bundle branch block. The performance of the algorithm is assessed by measuring the morphologic variability before and after QRS time synchronization and ectopic QRS elimination. The variability is reduced by a factor of 0.36 for healthy control subjects, 0.38 for patients with myocardial infarction, and 0.41 for patients with bundle branch block. The proposed algorithm can be used to generate a representative QRS loop for each VCG record. This representative QRS loop can be used to visualize, compare, and further process VCG records for automatic VCG record classification.cs
dc.description.firstpageart. no. 1260074cs
dc.description.sourceWeb of Sciencecs
dc.description.volume14cs
dc.identifier.citationFrontiers in Physiology. 2024, vol. 14, art. no. 1260074.cs
dc.identifier.doi10.3389/fphys.2023.1260074
dc.identifier.issn1664-042X
dc.identifier.urihttp://hdl.handle.net/10084/154904
dc.identifier.wos001143509300001
dc.language.isoencs
dc.publisherFrontiers Media S.A.cs
dc.relation.ispartofseriesFrontiers in Physiologycs
dc.relation.urihttps://doi.org/10.3389/fphys.2023.1260074cs
dc.rights© 2024 Kijonka, Vavra, Penhaker and Kubicek. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.cs
dc.rights.accessopenAccesscs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectdigital filteringcs
dc.subjectECGcs
dc.subjectintra-individualitycs
dc.subjectisoelectric line detectioncs
dc.subjectQRS detectioncs
dc.subjectQRS loop alignmentcs
dc.subjectrepresentative QRS loopcs
dc.subjectVCGcs
dc.titleRepresentative QRS loop of the VCG record evaluationcs
dc.typearticlecs
dc.type.statusPeer-reviewedcs
dc.type.versionpublishedVersioncs

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