Body-Surface Atrial Signals Analysis Based on Spatial Frequency Distribution: Comparison Between Different Signal Transformations

Olivier Meste*, Stef Zeemering, Joël Karel, Theo Lankveld, Ulrich Schotten, Harry Crijns, Ralf Peeters, Pietro Bonizzi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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Abstract

In contrast to electrograms, Body-Surface Potential Mapping (BSPM) records the global atrial activity, at the expenses of a lower spatial accuracy. The aim of this study is to investigate whether BSPM recordings can discriminate persistent patients undergoing electrical cardiover-sion, based on the body-surface normalized AF spatial frequency distribution. High-density BSPMs (120 anterior, 64 posterior electrodes) were recorded in 63 patients with persistent AF. For each patient and electrode recording, the frequency content of AF was analyzed on the raw signal, and also by means of the normalized correlation function, and by Singular Spectrum Analysis (SSA). In order to compare the body-surface spatial distributions of AF frequency in all patients, these distributions were first normalized, before performing statistical analysis. We found that the distribution of AF frequency on the body-surface, and its interpretation, are strongly dependent on the specific method employed. Moreover, the estimated body-surface AF frequency was greater over the central posterior and the right anterior BSPM locations. Finally, SSA-based decomposition followed by frequency analysis could discriminate AF patients recurring 4 to 6 weeks after electrical cardioversion from those who did not, based on the frequency content in the proximity of V1.
Original languageEnglish
Title of host publication2021 Computing in Cardiology (CinC)
PublisherIEEE
Pages1-4
Number of pages4
ISBN (Print)978-1-6654-6721-6
DOIs
Publication statusPublished - 15 Sept 2021
EventConference on Computing in Cardiology (CinC) - Hotel Passage, Brno, Czech Republic
Duration: 12 Sept 202115 Sept 2021

Publication series

SeriesComputing in Cardiology
Volume48
ISSN2325-8861

Conference

ConferenceConference on Computing in Cardiology (CinC)
Country/TerritoryCzech Republic
CityBrno
Period12/09/2115/09/21

Keywords

  • Correlation
  • Electric potential
  • Electrodes
  • Frequency estimation
  • Graphical models
  • Heart
  • Torso
  • FIBRILLATION

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