A Dynamic Systems Approach for Detecting and Localizing of Infarct-Related Artery in Acute Myocardial Infarction Using Compressed Paper-Based Electrocardiogram (ECG). Academic Article uri icon


  • Timely evaluation and reperfusion have improved the myocardial salvage and the subsequent recovery rate of the patients hospitalized with acute myocardial infarction (MI). Long waiting time and time-consuming procedures of in-hospital diagnostic testing severely affect the timeliness. We present a Poincare pattern ensemble-based method with the consideration of multi-correlated non-stationary stochastic system dynamics to localize the infarct-related artery (IRA) in acute MI by fully harnessing information from paper-based Electrocardiogram (ECG). The vectorcardiogram (VCG) diagnostic features extracted from only 2.5-s long paper ECG recordings were used to hierarchically localize the IRA-not mere localization of the infarcted cardiac tissues-in acute MI. Paper ECG records and angiograms of 106 acute MI patients collected at the Heart Artery and Vein Center at Fresno California and the 12-lead ECG signals from the Physionet PTB online database were employed to validate the proposed approach. We reported the overall accuracies of 97.41% for healthy control (HC) vs. MI, 89.41 9.89 for left and right culprit arteries vs. others, 88.2 11.6 for left main arteries vs. right-coronary-ascending (RCA) and 93.67 4.89 for left-anterior-descending (LAD) vs. left-circumflex (LCX). The IRA localization from paper ECG can be used to timely triage the patients with acute coronary syndromes to the percutaneous coronary intervention facilities.

published proceedings

  • Sensors (Basel)

author list (cited authors)

  • Le, T. Q., Chandra, V., Afrin, K., Srivatsa, S., & Bukkapatnam, S.

citation count

  • 7

complete list of authors

  • Le, Trung Q||Chandra, Vibhuthi||Afrin, Kahkashan||Srivatsa, Sanjay||Bukkapatnam, Satish

publication date

  • July 2020