Comparison and analysis of different ECG denoising methods

Abstract

With the improvement of medical level, electrocardiogram (ECG) is widely used for disease diagnosis. A lot of pathological and physiological information is contained in the ECG, which can be used to record the point activity of normal human heart and diagnose various heart disease. However, the acquired ECG signals are always contaminated with noise which caused by acquisition equipment or other circumstance. Therefore, Efficient denoising method is very important. In this paper, three typical ECG signal denoising methods are listed, including FIR filtering, wavelet filtering and EMD filtering. In this paper, the principles of the three filtering methods are introduced in detail, and their effects are compared. By comparison, it intuitively shows the processing effects of each method on ECG signals. Meanwhile, a simple Butterworth filter is designed to denoise a standard wave, which represents the logic knowledge related to denoising. It is very significant for the medical signal processing field and help to research more effective signal processing methods.