Topology and random-walk network representation of cardiac dynamics for localization of myocardial infarction

Trung Q. Le, Satish T.S. Bukkapatnam, Bruce Benjamin, Brek A. Wilkins, Ranga Komanduri

Research output: Contribution to journalArticle

13 Scopus citations


While detection of acute cardiac disorders such as myocardial infarction (MI) from electrocardiogram (ECG) and vectorcardiogram (VCG) has been widely reported, identification of MI locations from these signals, pivotal for timely therapeutic and prognostic interventions, remains a standing issue. We present an approach for MI localization based on representing complex spatiotemporal patterns of cardiac dynamics as a random-walk network reconstructed from the evolution of VCG signals across a 3-D state space. Extensive tests with signals from the PTB database of the PhysioNet databank suggest that locations of MI can be determined accurately (sensitivity of ∼88% and specificity of ∼92%) from tracking certain consistently estimated invariants of this random-walk representation.

Original languageEnglish
Article number6491458
Pages (from-to)2325-2331
Number of pages7
JournalIEEE Transactions on Biomedical Engineering
Issue number8
Publication statusPublished - 5 Aug 2013



  • Cardiac dynamics
  • myocardial infarction localization
  • vectorcardiogram (VCG) octant network

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