Abstract
Atrial fibrillation (AF) is the most common arrhythmia in the heart. Two main types of AF are defined as paroxysmal and persistent. In this paper, we present a method to discriminate between the characteristics of paroxysmal and persistent using tensor decompositions of a multi-channel electrocardiogram (ECG) signal. For this purpose, ECG signals are segmented by applying a Hilbert transform on the thresholded signal. Dynamic time warping is used to align the separated segments of each channel and then a tensor is constructed with three dimensions as time, heartbeats and channels. A Canonical polyadic decomposition with rank 2 is computed from this tensor and the resulting loading vectors describe the characteristics of paroxysmal and persistent AF in these three dimensions. The time loading vector reveals the pattern of a single P wave or abnormal AF patterns. The heartbeat loading vector shows whether the pattern is present or absent in a specific beat. The results can be used to distinguish between the patterns in paroxysmal AF and persistent AF.
Original language | English |
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Title of host publication | 28th European Signal Processing Conference (EUSIPCO 2020) |
Place of Publication | Amsterdam (Netherlands) |
Publisher | Eurasip |
Pages | 1155-1159 |
Number of pages | 5 |
ISBN (Print) | 978-9-0827-9705-3 |
Publication status | Published - 1 Aug 2020 |
Event | EUSIPCO 2020: The 28th European Signal Processing Conference - Amsterdam, Netherlands Duration: 18 Jan 2021 → 22 Jan 2021 Conference number: 28th |
Conference
Conference | EUSIPCO 2020 |
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Country/Territory | Netherlands |
City | Amsterdam |
Period | 18/01/21 → 22/01/21 |
Other | Date change due to COVID-19 (former date August 24-28 2020) |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.