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Author Alonso-Atienza, F. ♦ Rojo-Alvarez, J.L. ♦ Alvarez, D. ♦ Moscoso, M. ♦ Garcia-Alberola, A.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2007
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science ♦ Technology ♦ Medicine & health
Subject Keyword Support vector machines ♦ Inverse problems ♦ Robustness ♦ Image reconstruction ♦ Electrocardiography ♦ Equations ♦ Heart ♦ Electrodes ♦ Bioelectric phenomena ♦ Virtual manufacturing
Abstract Recent endocardial mapping systems reconstruct an instantaneous image of the endocardial electrical activity performing the inverse problem of electrocardiography (IPE), which consists of estimating the endocardial surface potentials from intracavitary probe potentials. Even though the IPE has been long studied, it still being paid attention due to its ill-posed nature, and many different regularization techniques have been explored in this setting. In this study we analyzed support vector machines (SVM) as an alternative regularization technique regarding their robustness against ill-posed problems. We propose here two new SVM algorithms, specifically adapted to the ill-posing issues of the IPE, and develop the equations for endocardial mapping of transmembrane currents. We show, both in simple simulations and in a previously developed cellular automata, that the ill-posing robustness of the SVM is higher when compared to regularized approaches during the depolarization phase. In conclusion, the properties of the developed SVM algorithms stand for an appropriate framework for addressing the IPE.
Description Author affiliation: Hosp. Univ. Virgen de la Arrixaca, Murca (Garcia-Alberola, A.) || Univ. Rey Juan Carlos, Madrid (Alonso-Atienza, F.; Rojo-Alvarez, J.L.) || Univ. Carlos III de Madrid, Leganes (Alvarez, D.; Moscoso, M.)
ISBN 9781424425334
ISSN 02766547
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2007-09-30
Publisher Place USA
Rights Holder Computers in Cardiology(CinC)
Size (in Bytes) 1.39 MB
Page Count 4
Starting Page 121
Ending Page 124


Source: IEEE Xplore Digital Library