title: Genetic algorithms for dipole location of fetal magnetocardiography.
abstract: In this paper, we explore the use of Maximum Likelihood (ML) method with Genetic Algorithms (GA) as global optimization procedure for source reconstruction in fetal magnetocardiography (fMCG) data. A multiple equivalent current dipole (ECD) model was used for sources active in different time samples. Inverse solutions across time were obtained for a single-dipole approximation to estimate the trajectory of the dipole position. We compared the GA and SIMPLEX methods in a simulation environment under noise conditions. Methods are applied on a real fMCG data. Results show robust estimators of the cardiac sources when GA is used as optimization technique.
authors.forename: D
authors.initials: D
authors.lastname: Escalona-Vargas
authors.forename: P
authors.initials: P
authors.lastname: Murphy
authors.forename: C L
authors.initials: CL
authors.lastname: Lowery
authors.forename: H
authors.initials: H
authors.lastname: Eswaran
mesh_terms: D000328:Adult; D000465:Algorithms; D005260:Female; D005323:Fetal Monitoring / Q000379:methods*; D006321:Heart / Q000196:embryology*; D006801:Humans; D016013:Likelihood Functions; D053798:Magnetocardiography / Q000379:methods*; D011247:Pregnancy; D059629:Signal-To-Noise Ratio