The Discrete Wavelet Transform Based Electrocardiographic Baseline Wander Reduction Method for Better Signal Diagnosis

Abstract

Noise reduction algorithms affect the performance of all electrocardiographic (ECG) signal-processing systems. This study deals with baseline wander (BW) interference reduction. Reducing this distortion without deforming the signal is difficult. To solve this problem we use the zero-phase high pass FIR equiripple filtering (ZPE) approach and discrete wavelet transform (DWT) correction method (DWTCM) was proposed. ZPE is used first to filter the signal then DWTCM is used for the remaining BW filtration by cutting the drift without ECG wave's distortion. The effectiveness was studied using the percentage root-mean-square difference (PRD) error, the standard deviation of the error, and the signal-to-noise ratio (SNR). Performance was compared to published methods of baseline wander reduction using synthetic as well as the natural signals from the MIT-BIH arrhythmia database. Results show a twofold reduction in the error of the suggested baseline-wander method compared to other methods