Unified neural network based pathologic event reconstruction using spatial heart model

Sándor M. Szilágyi, László Szilágyi, Attila Frigy, Levente K. Görög, Zoltán Benyó

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

Abstract

This paper presents a new way to solve the inverse problem of electrocardiography in terms of heart model parameters. The developed event estimation and recognition method uses a unified neural network (UNN)-based optimization system to determine the most relevant heart model parameters. A UNN-based preliminary ECG analyzer system has been created to reduce the searching space of the optimization algorithm. The optimal model parameters were determined by a relation between objective function minimization and robustness of the solution. The final evaluation results, validated by physicians, were about 96% correct. Starting from the fact that input ECGs contained various malfunction cases, such as Wolff-Parkinson-White (WPW) syndrome, atrial and ventricular fibrillation, these results suggest this approach provides a robust inverse solution, circumventing most of the difficulties of the ECG inverse problem.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, Proceedings
Pages851-860
Number of pages10
Publication statusPublished - Dec 1 2007
Event12th Iberoamerican Congress on Pattern Recognition, CIARP 2007 - Vina del Mar-Valparaiso, Chile
Duration: Nov 13 2007Nov 16 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4756 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th Iberoamerican Congress on Pattern Recognition, CIARP 2007
CountryChile
CityVina del Mar-Valparaiso
Period11/13/0711/16/07

Keywords

  • Heart model
  • Inverse ECG problem
  • Unified neural network

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Szilágyi, S. M., Szilágyi, L., Frigy, A., Görög, L. K., & Benyó, Z. (2007). Unified neural network based pathologic event reconstruction using spatial heart model. In Progress in Pattern Recognition, Image Analysis and Applications - 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, Proceedings (pp. 851-860). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4756 LNCS).