Imaging the electrical activity of the heart using a Kalman filter based approach: Comparison of results using different STM´s

Kalman filter based solutions have been of particular interest in inverse problem of Electrocardiography (ECG) in recent years. One of the major problems with this approach however is the determination of the state transition matrix (STM) that relates the epicardial potentials at the current time instant to the potentials at the previous time instant. In this work, we use the solutions of Tikhonov regularization and Bayes-MAP algorithm to construct a STM, and we use these STMs in Kalman filtering. Our results indicate that the Kalman filter that uses a STM obtained from Bayes-MAP solutions produces accurate solutions.