一种基于提升小波和中值滤波的心电去噪方法  

An Electrocardiogram Signals De-Noising Method Based on Lifting Wavelet and Median Filtering

作　　者：翁羽洁[1] 丁勇[2] 孙立艳[3] 杨涛[1] 

机构地区：[1]南京医科大学生物医学工程学院,南京210029 [2]南京医科大学数学与计算机科学学院,南京210029 [3]东南大学电子科学与工程学院,南京210096

出　　处：《北京生物医学工程》2010年第5期465-469,共5页Beijing Biomedical Engineering

摘　　要：小波变换在心电去噪中有非常好的效果,但传统的小波变换计算量大,不利于实时处理和嵌入式系统的实现,提升小波是一种快速有效的小波变换的实现方法,本文提出了一种运用提升小波和中值滤波去除心电信号工频干扰、肌电干扰和基线漂移三种噪声的方法。该方法运用提升小波对含噪声的心电信号做三层分解,并根据小波基的特性在不同层次采用不同的小波基,去除心电信号的工频干扰和肌电干扰;对第三层分解后得到的数据做中值滤波,去除心电信号的基线漂移。将以上方法与传统的小波方法相比,去噪结果表明两者去噪效果相当,但提升方法运算速度有很大的提升。结果证实将提升小波与中值滤波方法结合可以有效地去除心电信号的工频干扰、肌电干扰和基线漂移,而且可以较大地提高运算速度,便于进行实时处理和嵌入式系统的实现。Wavelet transform performs very well in removing noise of ECG, but the traditional wavelet transform costs a large number of calculations, it is inconvenient to real-time processing and embedded systems implementation. The lifting wavelet is a fast and effective implementation of wavelet transform. This article introduces an ECG de-noising method using lifting wavelet and median filtering. In this method, the lifting wavelet was used for three-level decomposition to ECG signals, and different wavelet bases were chosen to remove 50Hz frequency interference and EMG interference at different levels. We used the median filtering method to the data obtained after third level decomposition to remove baseline drift. Compare de-noising results of the above method with the traditional wavelet method, it was indicated that the de-noising results were equivalent, however the computing speed of the proposed method was improved greatly. Combination of lifting wavelet and median filtering gives a very good method to remove 50Hz frequency interference, EMG interference and baseline drift, and it also can improve computing speed, makes it ease of real-time processing and embedded system implementations.

关 键 词：心电 提升小波 中值滤波 

分 类 号：R318.04[医药卫生—生物医学工程]