Zhao Wei, Xiao Shixiao, Zhang Baocan, Huang Xiaojing, You Rongyi
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2015 Dec;32(6):1179-84.
Electrocardiogram (ECG) signals are susceptible to be disturbed by 50 Hz power line interference (PLI) in the process of acquisition and conversion. This paper, therefore, proposes a novel PLI removal algorithm based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD). Firstly, according to the morphological differences in ECG waveform characteristics, the noisy ECG signal was decomposed into the mutated component, the smooth component and the residual component by MCA. Secondly, intrinsic mode functions (IMF) of PLI was filtered. The noise suppression rate (NSR) and the signal distortion ratio (SDR) were used to evaluate the effect of de-noising algorithm. Finally, the ECG signals were re-constructed. Based on the experimental comparison, it was concluded that the proposed algorithm had better filtering functions than the improved Levkov algorithm, because it could not only effectively filter the PLI, but also have smaller SDR value.
心电图（ECG）信号在采集和转换过程中容易受到50Hz电源线干扰（PLI）的影响。因此，本文提出了一种基于形态分量分析（MCA）和总体经验模态分解（EEMD）的新型PLI去除算法。首先，根据心电图波形特征的形态差异，利用MCA将含噪心电图信号分解为突变分量、平滑分量和残余分量。其次，对PLI的本征模函数（IMF）进行滤波。采用噪声抑制率（NSR）和信号失真率（SDR）来评估去噪算法的效果。最后，对心电图信号进行重构。通过实验比较得出，所提算法比改进的Levkov算法具有更好的滤波功能，因为它不仅能有效滤除PLI，而且SDR值更小。
