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.
Multiresolution Minimization of Renyi's Mutual Information for fetal-ECG Extraction / Mammone, N.; Inuso, G.; Morabito, F. C.; Azzerboni, A.; LA FORESTA, Fabio. - 193 (1):(2009), pp. 50-59. (Intervento presentato al convegno WIRN 2008 tenutosi a Vietri S. M. (SA), Italy nel May 22-24) [10.3233/978-1-58603-984-4-50].
Multiresolution Minimization of Renyi's Mutual Information for fetal-ECG Extraction
N. MAMMONE;F. C. MORABITO;LA FORESTA, Fabio
2009-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
