Characterization of Cardio signals by time-frequency domain analysis

TL;DR

This paper combines time-frequency analysis with attractor reconstruction to effectively characterize and distinguish ECG signals from healthy individuals and heart failure patients.

Contribution

It introduces a novel approach that integrates wavelet transforms and integer lag plots for improved ECG signal analysis and classification.

Findings

Wavelet transform enhances ECG signal features for analysis.

Integer lag plots effectively differentiate between NHP and CHFP signals.

The method improves the characterization of complex nonlinear ECG dynamics.

Abstract

Long term behavior of nonlinear deterministic continuous time signals can be studied in terms of their reconstructed attractors. Reconstructed attractors of a continuous signal are meant to be topologically equivalent representations of the dynamics of the unknown dynamical system which generates the signal. Sometimes, geometry of the attractor or its complexity may give important information on the system of interest. However, if the trajectories of the attractor behave as if they are not coming from continuous system or there exists many spike like structures on the path of the system trajectories, then there is no way to characterize the shape of the attractor. In this article, the traditional attractor reconstruction method is first used for two types of ECG signals: Normal healthy persons (NHP) and Congestive Heart failure patients (CHFP). As common in such a framework, the reconstructed attractors are not at all well formed and hence it is not possible to adequately characterize their geometrical features. Thus, we incorporate frequency domain information to the given time signals. This is done by transforming the signals to a time frequency domain by means of suitable Wavelet transforms (WT). The transformed signal concerns two non homogeneous variables and is still quite difficult to use to reconstruct some dynamics out of it. By applying a suitable mapping, this signal is further converted into integer domain and a new type of 3D plot, called integer lag plot, which characterizes and distinguishes the ECG signals of NHP and CHFP, is finally obtained.