The use of genetic algorithms for solving the inverse problem of electrocardiography.
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.
Jiang
Mingfeng
M
Dept. of Biomed. Eng., Zhejiang Univ., Hangzhou, P.R. China.
Xia
Ling
L
Shou
Guofa
G
D000465:Algorithms; D004562:Electrocardiography / Q000379:methods*; D008433:Mathematics; D008957:Models, Genetic; D015203:Reproducibility of Results