Fetal electrocardiogram extraction by sequential source separation in the wavelet domain.

Maria G Jafari; Jonathon A Chambers

doi:10.1109/tbme.2004.842958

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Fetal electrocardiogram extraction by sequential source separation in the wavelet domain.

Maria G Jafari·Jonathon A Chambers

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Abstract

This paper addresses the problem of fetal electrocardiogram extraction using blind source separation (BSS) in the wavelet domain. A new approach is proposed, which is particularly advantageous when the mixing environment is noisy and time-varying, and that is shown, analytically and in simulation, to improve the convergence rate of the natural gradient algorithm. The distribution of the wavelet coefficients of the source signals is then modeled by a generalized Gaussian probability density, whereby in the time-scale domain the problem of selecting appropriate nonlinearities when separating mixtures of both sub- and super-Gaussian signals is mitigated, as shown by experimental results.

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Algorithms Body Surface Potential Mapping Diagnosis, Computer-Assisted Electrocardiography Female Fetal Monitoring Humans Models, Cardiovascular Models, Neurological Models, Statistical Pregnancy Signal Processing, Computer-Assisted Stochastic Processes Evaluation Study Journal Article Research Support, Non-U.S. Gov't

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Maria G Jafari, Jonathon A Chambers. 2005. Fetal electrocardiogram extraction by sequential source separation in the wavelet domain.. https://doi.org/10.1109/tbme.2004.842958

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