Online neural network training for automatic ischemia episode detection

D. K. Tasoulis, L. Vladutu, V. P. Plagianakos, A. Bezerianos, M. N. Vrahatis

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations


Myocardial ischemia is caused by a lack of oxygen and nutrients to the contractile cells and may lead to myocardial infarction with its severe consequence of heart failure and arrhythmia. An electrocardiogram (ECG) represents a recording of changes occurring in the electrical potentials between different sites on the skin as a result of the cardiac activity. Since the ECG is recorded easily and non-invasively, it becomes very important to provide means of reliable ischemia detection. Ischemic changes of the ECG frequently affect the entire repolarization wave shape. In this paper we propose a new classification methodology that draws from the disciplines of clustering and artificial neural networks, and apply it to the problem of myocardial ischemia detection. The results obtained are promising.

Original languageEnglish (US)
Pages (from-to)1062-1068
Number of pages7
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
StatePublished - Dec 9 2004
Event7th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2004 - Zakopane, Poland
Duration: Jun 7 2004Jun 11 2004


  • Ischemia episode detection
  • Online training

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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