Discrete Wavelet Transform Based Algorithm for Recognition of QRS Complexes

TL;DR

This paper introduces a Discrete Wavelet Transform-based algorithm for detecting QRS complexes in ECG signals, achieving high accuracy by effectively removing baseline wander and localizing wave features.

Contribution

The paper presents a novel application of DWT for QRS detection that improves accuracy and robustness in ECG analysis.

Findings

Achieved 98.1% detection rate of QRS complexes

Effective baseline wander removal using DWT

Validated performance on MIT BIH database

Abstract

This paper proposes the application of Discrete Wavelet Transform (DWT) to detect the QRS (ECG is characterized by a recurrent wave sequence of P, QRS and T-wave) of an electrocardiogram (ECG) signal. Wavelet Transform provides localization in both time and frequency. In preprocessing stage, DWT is used to remove the baseline wander in the ECG signal. The performance of the algorithm of QRS detection is evaluated against the standard MIT BIH (Massachusetts Institute of Technology, Beth Israel Hospital) Arrhythmia database. The average QRS complexes detection rate of 98.1 % is achieved.