Analysis of Butterworth Filter For Electrocardiogram De-Noising Using Daubechies Wavelets

International Journal of Electronics and Communication Engineering
© 2020 by SSRG - IJECE Journal
Volume 7 Issue 4
Year of Publication : 2020
Authors : Samson D.Yusuf, Francis C. Maduakolam, Ibrahim Umar, Abdulmumini Z. Loko
How to Cite?

Samson D.Yusuf, Francis C. Maduakolam, Ibrahim Umar, Abdulmumini Z. Loko, "Analysis of Butterworth Filter For Electrocardiogram De-Noising Using Daubechies Wavelets," SSRG International Journal of Electronics and Communication Engineering, vol. 7,  no. 4, pp. 8-13, 2020. Crossref,


Electrocardiogram (ECG) examination has been identified as an important investigation in medical diagnosis and therapy of cardiovascular diseases. However, wrong interpretation of these signals may lead to wrong diagnosis and wrong medication that can worsen the patient's situation; this is caused by noise in the signals. So denoising becomes paramount to the Physicians for better diagnosis. In this study, an extensive analysis of the Butterworth filter for ECG denoising using the Daubechies wavelets was carried out using MATLAB version 2015a. Noisy ECG signals downloaded from under MIT-BIH arrhythmia database were de-noised using Butterworth filter 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 denoising using Butterworth filter for SNR, MSE, and SIR gives an average value of 1.63dB, 0.2036, and 0.259dB, respectively. This implies that the Butterworth filter in ECG denoising is poor in taking care of background noise, and it also allows co-channel interference. Even though it tends to maintain a good fit for the useful signal, it also creates image signals that are also noise and cannot be recommended for ECG signal denoising. Hospitals management and cardiac health centers must understand the importance of these parameters to select ECG denoising filters for optimum diagnosis and therapy.


Electrocardiogram, Daubechies Wavelets, Butterworth Filter, De-Noising, Signals, noise interference.


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