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Fundamental Frequency and Regularity of Cardiac Electrograms With Fourier Organization Analysis

Dominant frequency analysis (DFA) and organization analysis (OA) of cardiac electrograms (EGMs) aims to establish clinical targets for cardiac arrhythmia ablation. However, these previous spectral descriptions of the EGM have often discarded relevant information in the spectrum, such as the harmonic...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2010-09, Vol.57 (9), p.2168-2177
Main Authors: Barquero-Pérez, Óscar, Rojo-Álvarez, José Luis, Caamaño, Antonio J., Goya-Esteban, Rebeca, Everss, Estrella, Alonso-Atienza, Felipe, Sánchez-Muñoz, Juan José, García-Alberola, Arcadi
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Language:English
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Summary:Dominant frequency analysis (DFA) and organization analysis (OA) of cardiac electrograms (EGMs) aims to establish clinical targets for cardiac arrhythmia ablation. However, these previous spectral descriptions of the EGM have often discarded relevant information in the spectrum, such as the harmonic structure or the spectral envelope. We propose a fully automated algorithm for estimating the spectral features in EGM recordings This approach, called Fourier OA (FOA), accounts jointly for the organization and periodicity in the EGM, in terms of the fundamental frequency instead of dominant frequency. In order to compare the performance of FOA and DFA-OA approaches, we analyzed simulated EGM, obtained in a computer model, as well as two databases of implantable defibrillator-stored EGM. FOA parameters improved the organization measurements with respect to OA, and averaged cycle length and regularity indexes were more accurate when related to the fundamental (instead of dominant) frequency, as estimated by the algorithm ( p
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2010.2049574