Estimation and Prediction of Propafenone on The Termination of Atrial Fibrillation by State-space Models

Abstract

Atrial fibrillation (AF) is the most frequent cardiac arrhythmia seen in clinical practice. Several therapeutical approaches have been developed to terminate the AF and the effects are evaluated by the reduction of the wavelet number after the treatments. In this paper, the state-space model was developed and applied to estimate the effects of pharmacological therapy on AF. Recordings (224-site bipolar recordings) of plaque electrode arrays placed on the right and left atria of pigs with sustained AF induced by rapid atrial-pacing were used to train and test the state-space models. The cardiac mapping data from five pigs treated with intravenous administration of antiarrhythmia drug, propafenone (PPF), were evaluated. The recordings of cardiac activity before the drug treatment were input to the model and the model output reported the estimated wavelet number of atria after the drug treatment. The results show that the predicting accuracy can reach 90%. It is expected that the developed state-space model can be further extended to assist the clinical staffs to estimate the effects of treatments for the AF patients in the future.