摘要
基线漂移对ECG采样信号的ST段特征信息准确提取带来很大困难。利用小波变换的良好分辨率分析特性,提出基于多分辨率分析的ECG基线漂移矫正算法。根据ECG多尺度分解后的高尺度细节信息特点,采用二次样条小波对采样ECG信号进行多尺度分解,然后选择高尺度下的细节信息进行自适应滤波,最后进行多尺度重构,实现消噪目的。多次实验结果表明,该算法能有效矫正ECG的基线漂移,且保持信号低频部分特征信息,这为准确提取ECG信号的ST段特征信息奠定了基础。
It is difficult to extract the character information of the ST segment from the sampled ECG contaminated by baseline drift. According to the good multi-resolution analysis character of wavelet, an ECG baseline drift depress algorithm based on multi-resolution analysis is introduced. Using the quadratic spline wavelet, the sampled ECG signal is multi-scale transformed, the adaptive de-noise is applied to detail information under higher scales, and then the signal is re-composed to filter the noise. Experiments indicate that the algorithm can efficiently depress the ECG baseline drift and keep the valuable ECG characteristic information in ECG low frequency section, which provides the base to accurately extract the ST segment information from the ECG.
出处
《计算机工程与设计》
CSCD
北大核心
2008年第13期3482-3484,共3页
Computer Engineering and Design
基金
广东工业大学博士基金项目(053043)
关键词
多分辨率分析
心电信号
基线漂移
细节信息
消噪
multi-resolution analysis
ECG
baseline drift
detailed information
de-noise
