Fusion of body surface potential and body surface Laplacian signals for electrocardiographic imaging

Various approaches to the solution to the inverse problem of electrocardiog raphy have been proposed over the years. Recently, the use of inverse algor ithms using measured body surface Laplacians has been proposed, and in vari ous studies this technique has been shown to outperform the traditional use of body surface potentials in certain model problems. In this paper, we co mpare the use of body surface potentials and body surface Laplacians on tno model problems with different assumed cardiac sources. For the spherical c ap model problems,vith an anterior source. the epicardial estimates using b ody surface potentials had smaller average relative errors than when body s urface Laplacians were used. For the spherical cap model problems with a po sterior source. the epicardial estimates using body surface potential or bo dy surface Laplacian sensors generally produced similar relative errors. Fo r the radial dipole model, the epicardial estimates using body surface Lapl acians had smaller errors than when body surface potentials were used. We i ntroduce a fusion algorithm that combines the different types of signals an d generally produces a good estimate for both model problems.