基于形态分量分析和集合经验模态分解的心电信号工频干扰消除法

发布时间：2018-01-16 05:10

  本文关键词：基于形态分量分析和集合经验模态分解的心电信号工频干扰消除法　出处：《生物医学工程学杂志》2015年06期 　论文类型：期刊论文

  更多相关文章： 工频干扰 心电信号 形态分量分析 集合经验模态分解

【摘要】：针对心电信号(ECG)在采集和转换的过程中容易受到工频干扰(PLI)的问题,提出了一种基于形态分量分析(MCA)和集合经验模态分解(EEMD)的PLI消除新算法。首先根据ECG特征波形的形态差异性,利用MCA将其分解为突变成分、平滑成分和残余白噪声成分,然后对含PLI的平滑成分进行EEMD,再滤除PLI的本征模态函数(IMF),最后重构ECG信号。文中采用噪声抑制率(NSR)和信号失真率(SDR)来评价算法的降噪效果。通过实验发现,该算法不仅能够有效地滤除工频干扰,而且SDR值较小,滤波效果优于改进的Levkov算法。
[Abstract]:In order to solve the problem that electrocardiogram (ECG) is easy to be interfered with by power frequency in the process of acquisition and conversion. A new PLI cancellation algorithm based on morphological component analysis (MCA) and set empirical mode decomposition (EEMD) is proposed. Firstly, according to the morphological differences of ECG characteristic waveforms, a new algorithm is proposed. It is decomposed into mutants, smooth components and residual white noise components by MCA, then the smooth components containing PLI are processed by EEMD, and then the intrinsic mode function of PLI is filtered. Finally, the ECG signal is reconstructed. The noise suppression rate (NSRR) and the signal distortion rate (SDR) are used to evaluate the noise reduction effect of the algorithm. The experimental results show that the algorithm can not only filter the power frequency interference effectively. Moreover, the SDR value is small and the filtering effect is better than the improved Levkov algorithm.
【作者单位】： 集美大学诚毅学院;集美大学理学院;
【基金】：福建省自然科学基金项目资助(2012J01280) 福建省中青年教师教育科研基金资助(JA13373,JA15653)
【分类号】：R540.4;TN911.7
【正文快照】： 引言心电信号(electrocardiogram,ECG)在诊断心血管疾病、评估各种治疗方法的有效性等临床应用中有重要意义[1-3]。体表采集到的ECG是一种非线性非平稳的微弱信号,易受到来自外界的各种干扰,主要有工频干扰(power line interference,PLI)、肌电干扰和基线漂移等,降低了正常诊，

本文编号：1431667