摘要
为了有效去除心电信号中的干扰噪声,对信号特征点进行准确标定,采用小波变换的阈值去噪算法和时域峰值定位算法进行心电信号处理.利用bior3.7小波按照Mallat算法对ECG信号进行分解,结合软硬阈值与小波重构的算法对信号进行去噪处理,给出了小波变换与时域峰值定位结合的算法检测各特征点.仿真结果表明小波阈值算法能有效去除心电信号中的干扰噪声,保留心电信号的有效信息,基于小波变换的时域峰值定位算法能准确检测出心电信号中的特征点.
For effectively eliminating noise of signal and accurately demarcating characteristic points of signal,denoising algorithm of wavelet transform with threshold and algorithm of time domain peak orientation are adopted to process ECG signal.The bior3.7 wavelet is used to decompose ECG signal according to Mallat algorithm,then algorithm for wavelet reconstruction with combination of soft and hard threshold is used to denoise,finally the algorithm of time domain peak orientation based on wavelet transform is used to demarcate feature points.Simulation results show that the noise is removed effectively,the ECG signal is retained,and feature points are accurately demarcated.
出处
《西安工业大学学报》
CAS
2012年第4期310-314,共5页
Journal of Xi’an Technological University
关键词
心电信号
小波变换
阈值去噪
特征点标定
ECG signal
wavelet transform
threshold denoise
demarcation of feature points
