一种基于二次样条母小波函数的心电QRS复合波检测算法
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摘要
目的:由于QRS复合波是心电信号中最重要的特征波,它的特征信息是心脏病分析和诊断的重要依据。在心电信号的分析、处理和特征信号提取中,QRS复合波的识别最为关键,心率的计算和分析以及P波和T波的检测都基于QRS复合波的精确定位。本研究通过二次样条小波函数的心电QRS复合波检测算法快速且准确地定位QRS复合波的特征点,为心电信号自动分析提供新的手段。方法:提出了一种基于二次样条小波函数的心电QRS复合波检测算法。采用二次样条母小波函数对心电信号作四尺度分解,得到相应尺度下的小波系数,在尺度三内,利用阈值搜索小波系数正负极大值对之间的过零点,确定R波位置,再在尺度一R波前后寻找局部模极大值对以确定QRS复合波起始点、终止点,通过调整阈值删除误检点,补偿漏检点,提高检测率。结果:采用MIT-BIH一些典型心电数据进行验证,取得99.59%准确率,与差分阈值、帯通滤波等算法相比具有方法简单、计算量小、抗干扰强,既达到了很高的准确率,又保证了运算时间。结论:本算法能够准确、快速地识别被噪声干扰的心电信号的QRS复合波,因而在心电信号的自动分析中有很好的应用前景和较高的实用价值。
Objective: the QRS wave is the most important characteristic waves of ECG signals,and the feature information is an important basis for heart disease diagnosis and analysis.In the analysis,processing and extraction the feature of the ECG signal,the identification is the key for QRS waves,the heart rate calculation and analysis,as well as the P-wave and T-wave detection are based on precise positioning of the QRS wave.This research through a quadratic spline mother wavelet function based ECG QRS detection algorithm is quickly and accurately locates the feature points of the QRS wave,and provides a new means of automatic analysis of ECG.Methods: a quadratic spline mother wavelet function based ECG QRS detection algorithm was Proposed.The quadratic spline mother wavelet function ECG signal decomposition in four dimensions,and get the corresponding scale of wavelet coefficient,in the scale of three,using the threshold search coefficient between the positive and negative maxima on the zero crossing,to determine the R wave position,and looking for local maxima in the scale of one before and after the R wave to delete incorrect points to determine QRS wave start points,end points,by adjusting the threshold to compensate for missed points to improve the detection rate.Results: With the MIT-BIH ECG database data validation,QRS complex wave correct detection rate of 99.59%,compared with differential threshold,band-pass filtering,this algorithm is simple,small amount of calculation,strong anti-interference,can achieve a high rate of accuracy,and ensure the operation time.Conclusions: This algorithm can accurately and quickly identify the noised QRS wave of ECG signal,and the automatic analysis of ECG signal has a good application prospect and a high practical value.
Objective: the QRS wave is the most important characteristic waves of ECG signals,and the feature information is an important basis for heart disease diagnosis and analysis.In the analysis,processing and extraction the feature of the ECG signal,the identification is the key for QRS waves,the heart rate calculation and analysis,as well as the P-wave and T-wave detection are based on precise positioning of the QRS wave.This research through a quadratic spline mother wavelet function based ECG QRS detection algorithm is quickly and accurately locates the feature points of the QRS wave,and provides a new means of automatic analysis of ECG.Methods: a quadratic spline mother wavelet function based ECG QRS detection algorithm was Proposed.The quadratic spline mother wavelet function ECG signal decomposition in four dimensions,and get the corresponding scale of wavelet coefficient,in the scale of three,using the threshold search coefficient between the positive and negative maxima on the zero crossing,to determine the R wave position,and looking for local maxima in the scale of one before and after the R wave to delete incorrect points to determine QRS wave start points,end points,by adjusting the threshold to compensate for missed points to improve the detection rate.Results: With the MIT-BIH ECG database data validation,QRS complex wave correct detection rate of 99.59%,compared with differential threshold,band-pass filtering,this algorithm is simple,small amount of calculation,strong anti-interference,can achieve a high rate of accuracy,and ensure the operation time.Conclusions: This algorithm can accurately and quickly identify the noised QRS wave of ECG signal,and the automatic analysis of ECG signal has a good application prospect and a high practical value.
引文
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[8]Moody GB,Mark RG.The MIT-BIH Arrhythmia Database on CD-ROM and Software for use with it[J].Computers in Cardiology,1991:185~188.Moody GB,Mark RG.MIT-BIT心率失常数据库光盘及使用软件[J].计算机心脏病学,1991:185~188.
[2]田絮资,杨建,黄力宇.基于数学形态学的心电信号R波检测算法[J].现代电子技术,2010.22(3):114-116.TIAN Xu-zi,YANG Jian,HUANG Li-Yu LIU.Detection algorithm of R wave inelectrocardiogram signal based on mathematical morphology[J].Modern Electronics Technique,2010.22(3):114-116.
[3]赵羿欧,刘扬.一种改进的差分阈值心电检测算法[J].计算机工程,2011.12(37):343-352.ZHAO Yi-ou,LIU Yang.Improved differentialthreshold ECG detection algorithm[J].Computer Engineering,2011.12(37):343-352.
[4]姚成,司玉娟,郎六琪,韩松洋.改进的基于小波变换的QRS波检测算法[J].吉林大学学报(信息科学版),2011.29(5):401-407.YAOCheng,SI Yu-juan,LANG Liu-qi,HAN Song-yang.Modifiedalgorithm of QRS wave detection based on wavelet transform[J].Journal of Jilin University(Information Science Edition),2011.29(5):401-407.
[5]胡广书.现代信号处理教程[M].北京:清华大学出版社,2004:246-247.HU Guang-shu.Modern signal processing tutorial[M].TsinghuaUniversity Press,2004:246-247.
[6]郑治真.小波变换及其MATLAB工具的应用[M].北京:地震出版社,2001:41-62.ZHENG Zhi-zhen.Wavelet transform and theapplication of MATLAB tools[M].Seismological Press,2001:41-62.
[7]Li C,Zheng C,Tai C.Detection of ECG characteristic Points usingwavelet transforms[J].IEEE Transactions on Biomedical Engineering,1995,42(l):20-28.Li C,Zheng C,Tai C.小波变换在检测心电图特征点的应用[J].IEEE生物医学工程,1995,42(l):20-28.
[8]Moody GB,Mark RG.The MIT-BIH Arrhythmia Database on CD-ROM and Software for use with it[J].Computers in Cardiology,1991:185~188.Moody GB,Mark RG.MIT-BIT心率失常数据库光盘及使用软件[J].计算机心脏病学,1991:185~188.
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