The effects of geometric errors on inverse ECG solutions using Kalman filter and Bayesian MAP estimation

Abstract

Geometric errors in inverse ECG are usually the errors occur in the mathematical model used for solution due to wrong interpretation of heart's position and size, conductivities of organs in the model and electrode positions. In this study the effects of geometric errors in inverse ECG problem for Kalman filter and Bayes-MAP methods are studied. Furthermore the method suggested by Kaipio et. al., which assumes that these geometric errors are additive noise and independent of the epicardial potentials, is implemented. With this method, the effects of geometric errors on Kalman filter and Bayes-MAP solutions are reduced at the cost of smoothing the wavefront.