Multiresolution minimization of renyi's mutual information for fetal-ECG extraction

Fabio La Foresta, Nadia Mammone, Giuseppina Inuso, Francesco C. Morabito, Andrea Azzerboni

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

Abstract

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. In literature, Independent Component Analysis (ICA) has been exploited to extract fECG. Wavelet-ICA (WICA), a technique that merges Wavelet decomposition and INFOMAX algorithm for Independent Component Analysis, was recently proposed to enhance fetal ECG extraction. In this paper, we propose to enhance WICA introducing MERMAID as the algorithm to perform independent component analysis because it has shown to outperform INFOMAX and the other standard ICA algorithms.

Original languageEnglish
Title of host publicationFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Pages50-59
Number of pages10
Volume193
Edition1
ISBN (Print)9781586039844
DOIs
Publication statusPublished - 2009

Publication series

NameFrontiers in Artificial Intelligence and Applications
Number1
Volume193
ISSN (Print)09226389

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Keywords

  • Fetal electrocardiogram
  • Independent Component Analysis
  • Wavelet Transform

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

La Foresta, F., Mammone, N., Inuso, G., Morabito, F. C., & Azzerboni, A. (2009). Multiresolution minimization of renyi's mutual information for fetal-ECG extraction. In Frontiers in Artificial Intelligence and Applications (1 ed., Vol. 193, pp. 50-59). (Frontiers in Artificial Intelligence and Applications; Vol. 193, No. 1). IOS Press. https://doi.org/10.3233/978-1-58603-984-4-50