Fetal magnetocardiographic signals extracted by 'signal subspace' blind source separation

In this paper, we apply independent component analysis to fetal magnetocardiographic data. In particular, we propose an extension of the "cumulant-based iterative inversion" algorithm to include a two-step "signal subspace" subdivision, which allows the user to control the number of components to be estimated by analyzing the eigenvalues distribution in an interactive way. Our results show that this method is a powerful means not only for the extraction of the cardiac signals from the background noise but also for a sharp separation of the baby's heart from the mother's.