Reliable Atrial Activity Extraction from ECG Atrial Fibrillation Signals

  • Felipe Donoso
  • Eduardo Lecannelier
  • Esteban Pino
  • Alejandro Rojas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7042)


Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical research, with a prevalence of 0.4% to 1% of the population. Therefore, the study of AF is an important research field that can provide great treatment improvements. In this paper we apply independent component analysis to a 12-lead electrocardiogram, for which we obtain a 12-source set. We apply to this set three different atrial activity (AA) selection methods based on: kurtosis, correlation of the sources with lead V1, and spectral analysis. We then propose a reliable AA extraction based on the consensus between the three methods in order to reduce the effect of anatomical and physiological variabilities. The extracted AA signal will be used in a future stage for AF classification.


atrial fibrillation atrial activity ECG ICA kurtosis correlation power spectral density 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Felipe Donoso
    • 1
  • Eduardo Lecannelier
    • 2
  • Esteban Pino
    • 1
  • Alejandro Rojas
    • 1
  1. 1.Department of Electrical EngineeringUniversity of ConcepcionConcepcionChile
  2. 2.Department of Internal MedicineUniversity of ConcepcionConcepcionChile

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