Spatial heart simulation and analysis using unified neural network

S. M. Szilágyi, L. Szilágyi, Z. Benyó

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

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 publicationAnalysis and Design of Intelligent Systems using Soft Computing Techniques
PublisherSpringer Verlag
Pages346-354
Number of pages9
ISBN (Print)9783540724315
DOIs
Publication statusPublished - Jan 1 2007

Publication series

NameAdvances in Soft Computing
Volume41
ISSN (Print)1615-3871
ISSN (Electronic)1860-0794

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computational Mechanics
  • Computer Science Applications

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  • Cite this

    Szilágyi, S. M., Szilágyi, L., & Benyó, Z. (2007). Spatial heart simulation and analysis using unified neural network. In Analysis and Design of Intelligent Systems using Soft Computing Techniques (pp. 346-354). (Advances in Soft Computing; Vol. 41). Springer Verlag. https://doi.org/10.1007/978-3-540-72432-2_35