System for Automatic Representation of Correlation Rhythmogram Dynamics of Long-Term ECG Signal Recordings

Abstract

In clinical practice, 24-hour monitoring of ECG records is often used to study heart rhythm. One of the methods for analyzing long-term ECG signal recordings is to present the signal in the form of a correlation rhythmogram. Using the analysis of scatterograms, static information is obtained, the processing of which gives primitive features and not enough information. These features are unable to describe the dynamic change in RR-intervals, which contains useful information about the nature of the heartbeat. We developed a system that allows to represent signals of long-term ECG recordings as a dynamic correlation rhythmogram. The algorithm allows to view the change in the dynamics of the heartbeat for 24 hours in a time less than 1 minute. Using our development as a tool for visualizing dynamic information of RR-intervals, specialists can extract unique information about the nature of the heartbeat and classify heart disorders with high accuracy.