Unified Neural Network Based Pathologic Event Reconstruction Using Spatial Heart Model
| Autor: | L.K. Gorog, Attila Frigy, Sándor M. Szilágyi, Zoltán Benyó, László Szilágyi |
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| Rok vydání: | 2007 |
| Předmět: |
Artificial neural network
Relation (database) medicine.diagnostic_test business.industry Inverse problem Machine learning computer.software_genre Robustness (computer science) medicine Minification Artificial intelligence business Algorithm Electrocardiography computer Event reconstruction Mathematics Event (probability theory) |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783540767244 CIARP |
| DOI: | 10.1007/978-3-540-76725-1_88 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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