ECG Denoising Using Wiener Filter and Kalman Filter

Abstract

Electrocardiogram (ECG) is a technique of understanding the functioning of heart. Each segment of the ECG signal is significant for the detection of different heart problems. However, some noises generally corrupt the ECG signal. We have performed a research on filters that denoise many kinds of noise observed in real ECG signal. Two filters are implemented to remove the noises, such as Wiener filter and Kalman filter. For better clarity, some performance parameters such as Mean Square Error (MSE), Percentage Root Mean Square Difference (PRD), Signal to Noise Ratio (SNR), Power Spectral Density (PSD), Spectrogram, Magnitude spectrum are used to compare the simulation outcomes. The outcomes of the simulation show that Wiener filter is an outstanding filter for denoising the ECG signal.