Fundamental frequency estimation in atrial fibrillation signals using correntropy and Fourier Organization Analysis

Advanced analysis of atrial fibrillation (AF) intra - cardiac electrograms aims to establish clinical targets for ablation. Frequency domain approaches, such as Dominant Frequency Analysis (DFA), estimate the dominant frequency to identify cardiac sites with high activation rates as ablation targets. However, they often discard relevant information in the spectrum, such as the harmonic structure or the spectral envelope. Moreover, these methods do not provide a complete characterization of complex atrial fibrillation signals. We propose to use the correntropy function to estimate the fundamental frequency, instead of dominant frequency, in order to quantify the activation rate of AF signals. We also propose to use the correntropy method combined with Fourier Organization Analysis (FOA), a method previously proposed to model fibril-latory signals, in order to estimate more than one fundamental frequency in complex signals which can be the result of the interaction of multiple wavefronts. The proposed approach was benchmarked by using pseudo-real AF signals for assessing their performance in a controlled environment. Two datasets of AF real signals were assembled, one with regular and simple signals, and another one with complex signals. Correntropy estimation of fundamental frequency, combined with FOA, allowed not only to characterize the periodicity of AF signals, but also to study more complex signals by modelling them with more than one component.