Next Article in Journal
Machine Learning to Quantify Physical Activity in Children with Cerebral Palsy: Comparison of Group, Group-Personalized, and Fully-Personalized Activity Classification Models
Next Article in Special Issue
Characterisation of Textile Embedded Electrodes for Use in a Neonatal Smart Mattress Electrocardiography System
Previous Article in Journal
Quantization-Mitigation-Based Trajectory Control for Euler-Lagrange Systems with Unknown Actuator Dynamics
Previous Article in Special Issue
Ambulatory Electrocardiographic Monitoring and Ectopic Beat Detection in Conscious Mice
Article

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

1
Industrial and Manufacturing Engineering, North Dakota State University, Fargo, ND 58102, USA
2
Industrial and Systems Engineering, Texas A&M University, College Station, TX 77843, USA
3
Heart Artery and Vein Center of Fresno, Fresno, CA 93722, USA
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(14), 3975; https://doi.org/10.3390/s20143975
Received: 20 May 2020 / Revised: 3 July 2020 / Accepted: 7 July 2020 / Published: 17 July 2020
(This article belongs to the Special Issue ECG Sensors)
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. View Full-Text
Keywords: electrocardiogram; nonlinear dynamic systems; computer-aided diagnosis electrocardiogram; nonlinear dynamic systems; computer-aided diagnosis
Show Figures

Figure 1

MDPI and ACS Style

Le, T.Q.; Chandra, V.; Afrin, K.; Srivatsa, S.; Bukkapatnam, S. A Dynamic Systems Approach for Detecting and Localizing of Infarct-Related Artery in Acute Myocardial Infarction Using Compressed Paper-Based Electrocardiogram (ECG). Sensors 2020, 20, 3975. https://doi.org/10.3390/s20143975

AMA Style

Le TQ, Chandra V, Afrin K, Srivatsa S, Bukkapatnam S. A Dynamic Systems Approach for Detecting and Localizing of Infarct-Related Artery in Acute Myocardial Infarction Using Compressed Paper-Based Electrocardiogram (ECG). Sensors. 2020; 20(14):3975. https://doi.org/10.3390/s20143975

Chicago/Turabian Style

Le, Trung Q., Vibhuthi Chandra, Kahkashan Afrin, Sanjay Srivatsa, and Satish Bukkapatnam. 2020. "A Dynamic Systems Approach for Detecting and Localizing of Infarct-Related Artery in Acute Myocardial Infarction Using Compressed Paper-Based Electrocardiogram (ECG)" Sensors 20, no. 14: 3975. https://doi.org/10.3390/s20143975

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop