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

Fetal Magnetocardiographic Signals Extracted by Signal Subspace Blind Source Separation.

Salustri C;
2005

Abstract

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
2005
Istituto di Scienze e Tecnologie della Cognizione - ISTC
Blind source separation
independent component analysis
magnetocardiography
signal subspace
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/29121
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