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

Sensors (Basel). 2020 Jul 17;20(14):3975. doi: 10.3390/s20143975.

Abstract

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.

Keywords: computer-aided diagnosis; electrocardiogram; nonlinear dynamic systems.

MeSH terms

  • Adult
  • Coronary Angiography
  • Coronary Vessels / diagnostic imaging
  • Electrocardiography*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Myocardial Infarction* / diagnosis
  • Systems Analysis