Research and application of ECG signal pretreatment based on wavelet de-noising technology

Abstract

Aiming to the ECG signal including the noise such as the baseline drift, power frequency interference, and muscle power interference, etc, it is not easy to diagnose the patient's illness condition, so, the wavelet de-noising algorithm used in ECG signal is research in detail. This paper studied the wavelet multi-resolution decomposition and de-noising methods, as well as analyzes the way of the threshold selection. Through the wavelet de-noising application to the ECG signal de-noising processing, the ECG signal that the noise polluted can be effectively filter by using the multi-resolution wavelet decomposition in selecting the wavelet threshold based on the Birge-Massart algorithm, and the de-noising effect is obvious better than the adaptive threshold selection.