Title :
Research and application of ECG signal pretreatment based on wavelet de-noising technology
Author_Institution :
Henan Coll. of Finance & Taxation, Zhengzhou, China
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.
Keywords :
diseases; electrocardiography; filtering theory; medical signal processing; noise pollution; patient diagnosis; signal denoising; signal resolution; wavelet transforms; Birge-Massart algorithm; ECG signal denoising processing; ECG signal pretreatment; adaptive threshold selection; baseline drift; denoising effect; filter; multiresolution wavelet decomposition; muscle power interference; noise pollution; patient diagnosis; patient illness condition; power frequency interference; wavelet denoising technology; wavelet threshold; Electrocardiography; Noise; Noise reduction; Time frequency analysis; Wavelet analysis; Wavelet transforms; ECG signal; Wavelet analysis; de-noising; signal reconstruction; threshold selection;
Conference_Titel :
Uncertainty Reasoning and Knowledge Engineering (URKE), 2012 2nd International Conference on
Conference_Location :
Jalarta
Print_ISBN :
978-1-4673-1459-6
DOI :
10.1109/URKE.2012.6319568
