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Author Kuzilek, J. ♦ Kremen, V. ♦ Lhotska, L.
Sponsorship IEEE Eng. Med. Biol. Soc.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Technology ♦ Medicine & health ♦ Engineering & allied operations
Subject Keyword Electrocardiography ♦ Noise ♦ Databases ♦ Correlation ♦ Noise reduction ♦ Estimation ♦ Independent component analysis
Abstract This paper explores differences between two methods for Blind Source Separation within frame of ECG de-noising. First method is Joint Approximate Diagonalization of Eigenmatrices, which is based on estimation of fourth order cross-cummulant tensor and its diagonalization. Second one is the statistical method known as Canonical Correlation Analysis, which is based on estimation of correlation matrices between two multidimensional variables. Both methods were used within method, which combines the Blind Source Separation algorithm with decision tree. The evaluation was made on large database of 382 long-term ECG signals and the results were examined. Biggest difference was found in results of 50 Hz power line interference where the CCA algorithm completely failed. Thus main power of CCA lies in estimation of unstructured noise within ECG. JADE algorithm has larger computational complexity thus the CCA perfomend faster when estimating the components.
Description Author affiliation: Dept. of Cybern., Czech Tech. Univ. in Prague, Prague, Czech Republic (Kuzilek, J.; Kremen, V.; Lhotska, L.)
ISBN 9781424479290
ISSN 1557170X
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-08-26
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 733.79 kB
Page Count 4
Starting Page 3857
Ending Page 3860

Source: IEEE Xplore Digital Library