We describe two new methods for the inverse problem of electrocardiography.
Both employ regularization with multiple constraints, rather than the stan
dard single-constraint regularization, In one method, multiple constraints
on the spatial behavior of the solution are used simultaneously. In the oth
er, spatial constraints are used simultaneously with constraints on the tem
poral behavior of the solution. The specific cases of two spatial constrain
ts and one spatial and one temporal constraint are considered in detail. A
new method, the L-Surface, is presented to guide the choice of the required
pairs of regularization parameters. In the case when both spatial and temp
oral regularization are used simultaneously, there is an increased computat
ional burden, and two methods are presented to compute solutions efficientl
y. The methods are verified by simulations using both dipole sources and me
asured canine epicardial data.