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Wavelet Transform Based Detection of the First-Degree Atrioventricular Block

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    0555154 - ÚPT 2022 RIV US eng C - Conference Paper (international conference)
    Smíšek, Radovan - Viščor, Ivo - Ivora, Adam - Bulková, V. - Maršánová, L. - Nejedlý, Petr - Koščová, Zuzana - Halámek, Josef - Jurák, Pavel - Plešinger, Filip
    Wavelet Transform Based Detection of the First-Degree Atrioventricular Block.
    2021 Computing in Cardiology (CinC). Vol. 48. New York: IEEE, 2021, č. článku 168. ISBN 978-166547916-5. ISSN 2325-8861. E-ISSN 2325-887X.
    [Computing in Cardiology 2021 /48./. Brno (CZ), 12.09.2021-15.09.2021]
    R&D Projects: GA TA ČR(CZ) FW01010305
    Institutional support: RVO:68081731
    Keywords : Wavelet Transform Based Detection * First-Degree Atrioventricular Block
    OECD category: Medical engineering
    https://ieeexplore.ieee.org/document/9662877

    Introduction: First-degree atrioventricular block (AVB I) is a pathology defined on ECG by a PR interval greater than 200 msec. This paper aims to automatically detect AVB I by measuring: the length of the PR interval. Method: Our method consists of the following steps: a) Records with atrial fibrillation or atrial flutter were excluded. b) QRS complexes were detected. c) QRS onset and T offset was detected for each ECG cycle. The median distance between QRS onset and the end of the previous T-wave is calculated (marked as X). d) QRSs were aligned and clustered according to morphological similarity. QRSs of the most frequent morphology were averaged. e) QRS onset and offset were detected for the averaged QRS. The signal between QRS onset and offset was replaced by a line intersected by the QRS onset and offset points. This signal was transformed by a wavelet transform. f) The P wave was detected in the transformed signal. The P onset was detected in the section from QRS onset minus X to the P wave position. g) AVB I was detected when the PR interval was longer than 200 msec. Results: The algorithm was set up and validated on private data and tested on publicly available databases. The algorithm achieves sensitivity 0.81, 0.81, 0.82, 0.84 and specificity 0.91, 0.90, 0.86, 0.93 for CPSC, CPSC-Extra, PTB-XL and Georgia database, respectively.
    Permanent Link: http://hdl.handle.net/11104/0329687

     
     
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