Abstract
Abstract Electrocardiogram (ECG) is a widely used tool for the early diagnosis and evaluation of cardiac disorders. The ECG signal is usually distorted during recording by different types of noise which may lead to incorrect diagnosis. Therefore, clear ECG signals are required to support good cardiac disorder diagnosing. In this paper, an efficient ECG denoising method using combined discrete wavelet with Savitzky-Golay (S-G) filter is proposed. The performance of S-G filter is studied in terms of polynomial degree and frame size, i.e. signal section. In addition, the performance of denoising wavelet is studied in term of mother wavelet type and wavelet order. The advantage of S-G filter is combined with discrete wavelet denoising method to get better denoising performance. The performance of denoising ECG are evaluated using signal to noise ratio (SNR) and percentage root mean square difference (PRD). For this we used simulated and gaussian white noise surrogated ECG signals. Our results show that combined S-G and wavelet filter denoising is noticeable better than the respective individual procedures. In addition, we found that the selection of frame size, order of the S-G filter and the wavelet type and order should be done carefully in order to get optimal results. It also holds true for the new filter that the optimal choice of filter parameters is a compromise between noise reduction and distortion.
Highlights
Electrocardiogram (ECG) is considered as one of the indispensable and low-cost tools for diagnosis and identifying cardiovascular diseases (CVD) by visual inspection of graphical representation of cardiac signal which is well-known as ECG signal
The MIT-BIM arrhythmia database has been considered to evaluate the performance of Discrete Wavelet Transform (DWT) filter, S-G filter and proposed method in denoising ECG signal [9]
The 100m is considered as a reference ECG signal, because it has normal beat rhythm, to investigate the best parameters of S-G and DWT filters. These parameters are considered for all other ECG signals, and the SNRout are caluclated overall data sets and averaged as in table 1
Summary
Electrocardiogram (ECG) is considered as one of the indispensable and low-cost tools for diagnosis and identifying cardiovascular diseases (CVD) by visual inspection of graphical representation of cardiac signal which is well-known as ECG signal. The main interest of this paper is to investigate the performance of DWT and S-G filter in denoising ECG signals. The SG filter is known as polynomial smoothing or least-squares smoothing filter, and it can preserve the high-frequency components of the signal [2]. This means that S-G filter can smooth out the signal by maintaining relevant properties of the original signal [2]. Efficient ECG denoising method based on combining DWT and S-G filter is proposed
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