Graphic Methods for Automatic Analysis of Nonlinear Characteristics of ECG Signals

Abstract

Automatic analysis of ECG signals makes it possible to assess the health status of patients, reducing the likelihood of human error and ensuring optimal and accurate results. The presentation of heart rate in the form of a dynamic series of RR intervals (intervals between successive heartbeats) and the application of graphical methods (Poincaré plot, Detrended Fluctuation Analysis and Multifractal Detrended Fuctuation Analysis) for analysis are an objective and non-invasive way to obtain information about the functional state of the organism. The present study presents the results of graphical analysis of RR interval series based on ECG signals of healthy and unhealthy subjects. The analysis is performed with the help of developed software for determining the nonlinear characteristics of the studied signals and the formation of graphical assessment of the health status of patients.