Is the Dominant Frequency Accurate Enough for Atrial Fibrillation Signals?

Aline Cabasson, Olivier Meste, Stef Zeemering, Ulrich Schotten, Pietro Bonizzi

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In noninvasive studies of atrial fibrillation (AF), especially in body surface potential map (BSPM) measurements, the dominant frequency (DF) is usually defined as the highest peak in the power spectrum, after prior cancellation or removal of the ECG components related to the ventricular activity. However, the power spectrum is often hampered by phase breaks presence in atrial signals due to either signal concatenation or to chaotic behavior. Fourier analysis (including multiple frequency components models) is used as a starting point to develop methods adapted to handle phase breaks. Fourier analysis and the average frequency derived from the phase of the analytic signal (within an AF cycle or globally) were selected as estimators of the single frequency model, and compared by means of simulations. It is found that for large phase breaks (±T/2 every half-second), and for a SNR of 5db, the 95 % confidence interval were smaller for the estimates based on the phase, within an AF cycle, of the analytic signal. For the more realistic multiple frequency model, the Fourier decomposition is extended by using a Least Mean Squares (LMS) adaptive algorithm, with or without imposing a constant magnitude. Slight differences in performances of the presented methods are exemplified on a single AF subject where the DF is computed over all the leads of the BSPM records.

Original languageEnglish
Title of host publication2022 Computing in Cardiology (CinC)
Number of pages4
Publication statusPublished - 2022
Event49th Computing in Cardiology Conference 2022 - Tampere Hall, Tampere, Finland
Duration: 4 Sept 20227 Sept 2022
Conference number: 49


Conference49th Computing in Cardiology Conference 2022
Abbreviated titleCinC 2022
Internet address


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