中文摘要：

心电信号（ECG）是临床诊断各种疾病的重要依据,但由于基线漂移等噪声的存在影响了其诊断的准确性.根据基线信号的特点和固有模态函数（IMF）的性质,提出一种基于经验模态分解（EMD）结合形态滤波的自适应滤波方法.该方法先对信号进行经验模态分解,然后对所选择的IMF分量进行形态滤波处理,将滤波后的结果作为自适应滤波器的参考输入信号,最后得到的输出误差信号即为去除基线漂移后的心电信号.通过与普通的EMD方法、基于EMD的自适应滤波方法对比,并采用MIT-BIH数据库中的心电数据进行了检验,实验结果表明该方法对于去除心电基线有较好的效果.

英文摘要：

ECG was an important basis for clinical diagnosis of diseases. But the noises, such as baseline wander, affected the accuracy of ECG diagnosis. According to the properties of baseline wander and intrinsic mode function （IMF）,a new method called adaptive filtering based on empirical mode decomposition （EMD） com- bined morphological filtering was proposed in the paper. First, ECG signal was decomposed into a series of IMFs by EMD, then those IMFs selected were processed further by the morphological filter. The filtering result was re- garded as the reference input signal. Finally, the error output signal was ECG signal removed the baseline wan- der. The proposed method was compared with common EMD, adaptive filter based on EMD, and it was tested by using MIT - BIH Database. The experiment results showed that the method was effective in removing ECG base- line wander.