The Use of Genetic Algorithms for Solving the Inverse Problem of Electrocardiography

Abstract

Reconstruction of the epicardial potentials from the body surface potentials constitutes one form of the ill-posed inverse problem of electrocardiography (ECG). In this paper, we investigate the use of genetic algorithms (GAS) for regularizing ill-posed ECG inverse problem. The result shows that, GAS cannot be used to regularized ill-posed problem without additional constraints, but combined with other methods or additional information about solutions, GAS is an efficient optimization technique for solving the ill-posed inverse problem. We adopt the Tikhonov regularized solutions as the additional information to construct the initial populations. This investigation suggests that the GAS may provide a useful tool for ECG inverse problem studies