小波变换和支持向量机相融合的ECG身份识别  

ECG human identification based on wavelet transforms and Support Vector Machine

作　　者：吕刚[1] 陈立[2] 

机构地区：[1]金华广播电视大学理工学院,浙江金华321000 [2]杭州电子科技大学,杭州310018

出　　处：《计算机工程与应用》2013年第24期195-199,共5页Computer Engineering and Applications

摘　　要：为了提高心电图(ECG)信号的身份识别正确率,提出一种小波变换和支持向量机相融合的ECG身份识别方法 (IWT-ABC-SVM)。采用一种小波阈值函数对ECG进行去噪处理,提取ECG特征,将ECG特征输入到支持向量机中进行学习,采用人工蜂群算法优化支持向量机参数,建立ECG的身份识别模型,采用MIT-BIH心电图数据进行仿真测试。仿真结果表明,相对于其他识别方法,IWT-ABC-SVM提高了ECG身份识别的正确率和可靠性。In order to improve the rate of human identification based on ECG, a novel ECG human identification approach （IWTABCSVM） is proposed based on wavelet analysis and Support Vector Machine. Wavelet threshold function is used to de noise the ECG, and the ECG features are extracted; the ECG features are input to Support Vector Machine to learn, and the pa rameters of Support Vector Machine are optimized by artificial bee colony algorithm; the human identification classifier is estab lished and the simulation experiment is carried out by using MITBIH ECG data. The results show that compared with other identification methods, the proposed method has imDroved the identification accuracy and reliability.

关 键 词：心电图信号 身份识别 小波去噪 人工蜂群算法 支持向量机 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]