基于经验模态分解和Hilbert变换的QRS综合波检测算法  

A QRS Detector Based on Empirical Mode Decomposition and Hilbert Transform

作　　者：朱伟芳[1] 赵鹤鸣[1] 俞一彪[1] 

机构地区：[1]苏州大学电子信息学院,苏州215021

出　　处：《中国生物医学工程学报》2010年第3期358-362,372,共6页Chinese Journal of Biomedical Engineering

摘　　要：提出一种新的有效结合经验模态分解(EMD)和Hilbert变换的QRS综合波检测算法。采用EMD将心电信号分解成一系列内蕴模式分量(IMFs),舍去对应于高频噪声的IMF1和IMF2,舍去对应于低频噪声的最后两个IMFs和趋势项,能有效地抑制高频噪声和基线漂移。将降噪后的信号进行Hilbert变换,得到对应的解析函数,利用其包络,进一步抑制高大P波、T波等对QRS综合波检测的影响,采用自适应阈值进行QRS综合波检测。经MIT-BIH Arrhythmia Database全部数据检测验证,平均正确检测率可达到99.78%,表明本算法具有较高的正确检测率和良好的抗噪性能。A novel QRS complex detection algorithm based on the EMD and Hilbert Transform was proposed in this paper.The EMD decomposed the electrocardiogram（ ECG） signal into a series of oscillatory components called intrinsic mode functions（IMFs）.IMF1 and IMF2 which contained high frequency noise were omitted.The last two IMFs and the residual were also omitted to decrease the low frequency noise.Then Hilbert transform was placed on the re-composed signal to get the analytic signal.An adaptive threshold was used to locate the QRS complex in the envelope of the analytic signal,minimizing the effects of large peaked P and T waves.The performance of the algorithm was tested using all 48 records from the MIT-BIH Arrhythmia Database and an averaged detection rate of 99.78% was achieved.

关 键 词：心电信号 经验模态分解 HILBERT变换 QRS综合波检测 

分 类 号：R318.04[医药卫生—生物医学工程]