Including sparse noisy epicardial potential measurements into Bayesian inverse electrocardiography

Imposition of a priori constraints is needed to combat the ill-posedness of the inverse problem of electrocardiography. Solutions to this problem have not yet achieved clinical utility. Extra measurements from catheters inserted into cardiac veins, even though quite sparse, may help increase accuracy and robustness. In this paper, we study various Bayesian methods to incorporate sparse epicardial measurements in solutions to the inverse problem.