Sampling Rate Independent Filtration Approach for Automatic ECG Delineation

TL;DR

This paper introduces a sampling rate independent filtration algorithm for automatic ECG delineation, capable of distinguishing various ECG wave morphologies, and compares it with existing methods like the à trous algorithm.

Contribution

The paper proposes a novel filtration approach that is sampling rate independent and adaptable for ECG delineation, improving robustness across different sampling conditions.

Findings

The proposed algorithm effectively distinguishes T, P, and QRS wave morphologies.

It performs comparably or better than the à trous algorithm.

Continuous wavelet transform with automatic adaptation enhances delineation accuracy.

Abstract

In this paper different types of ECG automatic delineation approaches were overviewed. A combination of these approaches was used to create sampling rate independent filtration algorithm for automatic ECG delineation that is capable of distinguishing different morphologies of T and P waves and QRS complexes. Created filtration algorithm was compared with algorithme \`a trous. It was investigated that continuous wavelets transform with proposed automatic adaptation for different sampling rates procedure can be used for delineation problem.