The use of the simulation results as a priori information to solve the inverse problem of electrocardiography for a patient

In the present work the epicardial potential distribution for an individual patient provided by the solution of the linear inverse problem of electrocardiography are shown. To obtain the solution, the Twomey regularization as well as the stochastic regularization were used. Both methods require a priori estimations. These estimations were provided by means of simulation of the cardiac activity on a personalized electrophysiological model of the patient. To estimate the quality of the results provided by each method, the inverse problem was solved with the simulated ECG, the solution being compared with the epicardial potentials obtained from the simulation. Twomey regularization tends to provide the better correspondence than the conventional Tikhonov 0-order regularization. The stochastic regularization provides the best correspondence with the reference data, being the most time-consuming of all the methods under consideration. Solving the inverse problem of electrocardiography provides a physician with the useful information about the electrophysiological processes in the heart of a patient