Surface ECG organization analysis to predict paroxysmal atrial fibrillation termination

  • Authors:

  • R. Alcaraz;J. J. Rieta

  • Affiliations:

  • E.U. Politécnica de Cuenca, Innovation in Bioengineering Research Group, University of Castilla-La Mancha, Campus Universitario, 16071 Cuenca, Spain;Biomedical Synergy, Electronic Engineering Department, Universidad Politécnica de Valencia, Campus de Gandia, 46730 Gandia, Spain

  • Venue:
  • Computers in Biology and Medicine
  • Year:
  • 2009

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Abstract

The aim of this work is to predict non-invasively if an AF episode terminates spontaneously or not by analyzing the increase of atrial activity organization prior to paroxysmal atrial fibrillation (PAF) termination. Sample entropy was selected as non-linear organization index. Synthetic PAF signals were used to evaluate the notable impact of noise in AA organization estimation. Three strategies to reduce noise, ventricular residues and enhance the atrial activity main features were proposed. The best prediction results were obtained through main atrial wave (MAW) organization estimation. The MAW can be considered as the fundamental waveform associated to the AA. The 92% of the terminating and non-terminating analyzed PAF episodes were correctly classified. Thereby, it can be concluded that the MAW non-linear analysis from the surface ECG is a reliable and useful tool to predict spontaneous PAF termination.