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A New Method for Estimating Cardiac Transmembrane Potentials from the Body Surface

Transmembrane potentials (TMPs) on the heart surface can be used to calculate body- surface potentials (BSPs) using a bidomain model, in order, for example, to assess the sensitivity of BSPs to TMP changes with pathology. Conversely, TMPs can be estimated from BSPs with inverse methods. In this study, a new inverse approach called regularized waveform identification (RWI) was developed that combines spatial regularization with temporal optimization to estimate TMPs from BSPs with greater accuracy than conventional regularization alone. TMPs were estimated throughout the T wave, using the realistic ventricle-torso model and heart-surface TMPs of the ECGSIM simulation package. We evaluated the sensitivity of our RWI approach to 1, 2, 5 and 10% electrical noise on the body surface. Relative errors (RE) of 0.98 were found. A 10% enlargement of the heart and position errors of ±1cm in all directions yielded REs of 0.97. Simulation results showed that this approach performed much better than traditional regularization methods alone and is robust in the presence of noise and geometric error. By incorporating temporal information, in the form of the basic TMP wave shape, estimation accuracy was enhanced while maintaining computational simplicity.