Altered nonlinear dynamics of atrial fibrillation detected after ablation

Kevin W. Sunderland, Adam E. Berman, Autumn M. Schumacher

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Atrial fibrillation (AF) consists of uncoordinated atrial and ventricular electrical activity. QuantifYing the nonlinear dynamics of AF is difficult since the QRS wave masks the P wave patterns on the electrocardiogram (ECG). The purpose of this project was to minimize the size of the QRS wave and analyze the remaining atrial ECG signal to better measure the nonlinear dynamics underlying AF A continuous single-lead ECG signal was digitally recorded during atrial myocardial tissue ablation in 19 adult AF patients. Thirty-second segments of AF were selected before and after ablation from each ECG recording. The ECG segments were processed with the adaptive singular value cancelation (ASVC) technique to reduce the size of the QRS wave. The remaining atrial signal was then analyzed with recurrence quantification analysis (RQA) to quantifY its nonlinear dynamics. The RQA variable, %determinism, significantly decreased after ablation (p=.042). This finding suggests that the processed AF signal contained less structure in the nonlinear domain after ablation of the atrial myocardial tissue. These results demonstrated that the ASVC technique reduced the size of the QRS wave allowing RQA to detect alterations in the nonlinear dynamics of the remaining atrial ECG signal after ablation.

Original languageEnglish (US)
Title of host publicationComputing in Cardiology
PublisherIEEE Computer Society
Pages809-812
Number of pages4
Volume41
EditionJanuary
StatePublished - 2014
Event41st Computing in Cardiology Conference, CinC 2014 - Cambridge, United States
Duration: Sep 7 2014Sep 10 2014

Other

Other41st Computing in Cardiology Conference, CinC 2014
CountryUnited States
CityCambridge
Period9/7/149/10/14

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Computer Science(all)

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