Applying the Method of Critical Fluctuations on Human Electrocardiograms

TL;DR

This paper applies the Method of Critical Fluctuations to human ECG signals, successfully distinguishing healthy individuals from myocardial infarction cases with high accuracy based on criticality analysis.

Contribution

The study demonstrates the effectiveness of the Method of Critical Fluctuations in analyzing ECG signals for health assessment, providing a novel application in cardiac diagnostics.

Findings

100% verification of myocardial infarction detection

88% agreement in healthy control characterization

Identification of specific symmetries in ECG autocorrelation profiles

Abstract

In this work we apply the Method of Critical Fluctuations (MCF)on human Electrocardiogram (ECG) time-series. The method is able to reveal critical characteristics, in terms of physical behavior, in experimentally recorded signals. Using the concept of criticality as basic criterion for the characterization of the recorded ECG as that of a healthy person, we find a 100% verification of the characterization Myocardial infarction. In contrary in the cases of the characterization Healthy control we find a 88% agreement. We also consider the autocorrelation function for the ECG time-series which obeys optimally the criteria of criticality and we observe the appearance of specific characteristic symmetries in the corresponding profile.