Characterization of Atrial Fibrillation Episodes Using a Point Process Model

The purpose of the present study is to introduce a point process model for characterizing the pattern of atrial fibrillation (AF) episodes. A variant of the bivariate Hawkes process is proposed, accounting for clustered episodes. The model parameters are inferred by the maximum likelihood method. The goodness-of-fit analysis show that model fits the data in most of the recordings (27 out of 32). The information provided by this approach is complementary to AF burden.