ICASSP'98 Multidimensional independent component analysis.

ICASSP '98. Multidimensional independent component analysis.


In this ICASSP '98 paper, I suggest extending the idea independent component analysis (ICA) to a more general idea of multidimensional independent component analysis (MICA). This idea comes to mind very naturally when processing ECG recordings from a pregnant woman. The source separation task consists in separating the maternal signal and the fetal signal: a straightforward application of a source separation algorithm reveals that the maternal ECG signal and/or the fetal ECG signal behave as multidimensional components. This fact is probably known since the work of Widrow (LMS-based signal subtraction for extracting the fetal ECG). In the context of ICA/source separation, it is well documented in the 1995 paper Fetal electrocardiogram extraction by source subspace separation by De Lathauwer et al. which also points out the relevance of the notion of subspace associated to each component.

This page points to some Matlab code allowing to reproduce the experiment on a restricted data set as reported in the paper and to make another, even more convincing experiment, on the whole data set.

If you do not want to run the code for this last experiment and are only interested in checking the results of the MICA analysis on the whole data set, take a look at this figure (pdf file) which is in the same spirit as the figure of the ICASSP paper.

To run the experiments using Matlab, you need the following files:


Created: Feb. 20, 1998. Thanks for reporting any bug/problem. JFC.
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