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The non-invasive and radiation-free imaging of the electrical activity of theheart with Electrocardiography (ECG) or Magnetocardiography (MCG) can behelpful for physicians for instance in the localization of the origin ofcardiac arrhythmia. In this paper we compare two Kalman Filter algorithms forthe solution of a nonlinear state-space model and for the subsequent imagingof the activation/depolarization times of the heart muscle: the ExtendedKalman Filter (EKF) and the Unscented Kalman Filter (UKF). The algorithms arecompared for simulations of a (6×6) magnetometer array, a torso modelwith piecewise homogeneous conductivities, 946 current dipoles located in asmall part of the heart (apex), and several noise levels. It is found thatfor all tested noise levels the convergence of the activation times is fasterfor the UKF

Comparison of the Extended Kalman Filter and the Unscented Kalman Filter for Magnetocardiography activation time imaging