A new approach based on Wavelet-ICA algorithms for fetal electrocardiogram extraction

Bruno Azzerboni, Fabio La Foresta, Nadia Mammone, Francesco Carlo Morabito

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The fetal electrocardiogram (fECG) monitoring yields important information about the fetus condition during pregnancy and it consists in collecting electrical signals by some sensors on the body of the mother. The Independent Component Analysis (ICA) has been widely exploited to isolate the fECG, while wavelet transform has been used as post-processing tool. Here we propose to fit the recently developed Wavelet-ICA method, based on the joint use of Wavelet Analysis and ICA, to fECG extraction, in order to improve the extraction performance. We also show a comparison with other techniques and we discuss the advantages of the proposed method.

Original languageEnglish
Title of host publicationESANN 2005 Proceedings - 13th European Symposium on Artificial Neural Networks
Pages193-198
Number of pages6
Publication statusPublished - 2007
Event13th European Symposium on Artificial Neural Networks, ESANN 2005 - Bruges, Belgium
Duration: Apr 27 2005Apr 29 2005

Other

Other13th European Symposium on Artificial Neural Networks, ESANN 2005
Country/TerritoryBelgium
CityBruges
Period4/27/054/29/05

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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