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

Abstract: In order to improve the rate of human identification based on ECG, a novel ECG human identification approach（IWT-ABC-SVM） is proposed based on wavelet analysis and Support Vector Machine. Wavelet threshold function is used to denoise the ECG, and the ECG features are extracted; the ECG features are input to Support Vector Machine to learn, and the parameters of Support Vector Machine are optimized by artificial bee colony algorithm; the human identification classifier is established and the simulation experiment is carried out by using MIT-BIH ECG data. The results show that compared with other identification methods, the proposed method has improved the identification accuracy and reliability.

Key words: Electrocardiography（ECG） signal, human identification, wavelet denoise, artificial bee colony algorithm, Support Vector Machine（SVM）