Analysis of Savitzky-Golay Filter for Electrocardiogram De-Noising Using Daubechies Wavelets

Abstract

Electrocardiogram (ECG) examination is of great importance in medical diagnosis of the cardiac disease, but wrong interpretation due to noise interference in the signal could be dangerous as this may lead to wrong diagnoses of patient’s heart condition. De-noising helps to reduce the noise level for a better interpretation of the signals. In this study, an analysis of Savitzky-Golay (S-G) filter for ECG de-noising using Daubechies wavelets has been carried out using MATLAB version 2015a. Noisy ECG signals downloaded from physionet.org under MIT-BIH arrhythmia database was de-noised using S-G filter of polynomial order 9 to data frames of length 21 displayed in both time and frequency domains while a quantitative evaluation was carried out to check the performance of the filter under signal-to-noise ratio (SNR), mean square error (MSE) and signal-to-interference ratio (SIR). Results show that de-noising using S-G filter for SNR, MSE, and SIR gives an average value of 32.78dB, 0.0001 and 1852.358dB respectively. This implies that the S-G filter helps eliminates the background noise as well as maintaining a good fit for our data, and also do not allow co-channel interference from other radio transmitters, which makes it an excellent filter for ECG signal de-noising. Hospitals management and cardiac health centers most understand the importance of these parameters in the selection of de-noising filters for good quality ECG in diagnosis and treatment of cardiac patients.