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

abstract

• 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.

authors

• Bukkapatnam, Satish

published proceedings

• IEEE Trans Biomed Eng

author list (cited authors)

• Le, T. Q., Bukkapatnam, S., Benjamin, B. A., Wilkins, B. A., & Komanduri, R.

citation count

• 25

complete list of authors

• Le, Trung Q||Bukkapatnam, Satish TS||Benjamin, Bruce A||Wilkins, Brek A||Komanduri, Ranga

publication date

• August 2013

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Transactions on Biomedical Engineering  Journal

keywords

• Algorithms
• Data Interpretation, Statistical
• Diagnosis, Computer-Assisted
• Humans
• Myocardial Infarction
• Reproducibility Of Results
• Sensitivity And Specificity
• Vectorcardiography

Digital Object Identifier (DOI)

• 10.1109/TBME.2013.2255596

start page

• 2325

end page

• 2331

volume

• 60

issue

• 8

URL

• http://dx.doi.org/10.1109/tbme.2013.2255596