An improved wavelet threshold algorithm for ECG denoising.
- Author:
Xiuling LIU
;
Lei QIAO
;
Jianli YANG
;
Bin DONG
;
Hongrui WANG
- Publication Type:Journal Article
- MeSH:
Algorithms;
Arrhythmias, Cardiac;
Databases, Factual;
Electrocardiography;
Humans;
Signal Processing, Computer-Assisted;
Wavelet Analysis
- From:
Journal of Biomedical Engineering
2014;31(3):511-515
- CountryChina
- Language:Chinese
-
Abstract:
Due to the characteristics and environmental factors, electrocardiogram (ECG) signals are usually interfered by noises in the course of signal acquisition, so it is crucial for ECG intelligent analysis to eliminate noises in ECG signals. On the basis of wavelet transform, threshold parameters were improved and a more appropriate threshold expression was proposed. The discrete wavelet coefficients were processed using the improved threshold parameters, the accurate wavelet coefficients without noises were gained through inverse discrete wavelet transform, and then more original signal coefficients could be preserved. MIT-BIH arrythmia database was used to validate the method. Simulation results showed that the improved method could achieve better denoising effect than the traditional ones.