ПОРІВНЯЛЬНИЙ АНАЛІЗ ЕФЕКТИВНОСТІ МАТЕРИНСЬКИХ ВЕЙВЛЕТІВ ДЛЯ ЗНЕШУМЛЕННЯ СИГНАЛІВ ЕКГ

Abstract

Reducing the noise of the electrocardiogram (ECG) signal is crucial for accurate analysis and diagnosis of cardiovascular diseases. Discrete wavelet transform is an effective method for reducing ECG signal noise. However, the choice of the mother wavelet has a significant impact on the effectiveness of noise removal. This study aims to compare the performance of 105 mother wavelets from different wavelet families for ECG signal noise reduction using discrete wavelet transform.

A dataset of 100 random ECG signals was selected from a large-scale 12-lead Physionet electrocardiogram database for arrhythmia studies. Each ECG signal was subjected to a direct and inverse transformation, and the mean square errors of the transformation were calculated. Based on the calculations, the most efficient mother wavelet functions were selected.

Obtained results demonstrate that the choice of the mother wavelet has a significant impact on the conversion efficiency and, as a result, the elimination of ECG signal noise. The study revealed the most effective mother wavelets in general.

The results of this study provide valuable information on the selection of appropriate mother wavelets for ECG signal processing. The identified best mother wavelets can be used in practical applications to improve the accuracy of ECG signal analysis and diagnosis.