ECG identification based on Matching Pursuit

Author

Zhao, Zhidong ; Yang, Lei

Author_Institution

Coll. of Electron. & Inf., Hang Zhou DianZi Univ., Hangzhou, China

Volume

2

fYear

2011

fDate

15-17 Oct. 2011

Firstpage

721

Lastpage

724

Abstract

Electrocardiogram (ECG) reflects cardiac electrical activity, and varies from person to person, which could be used for biometrics identification. ECG biometrics identification algorithm is presented in this paper based on Matching Pursuit (MP) and Support Vector Machine (SVM). The ECG signal is decomposed into atoms by sparse decomposition with Gabor dictionary which contain ECG signal´s important information. SVM is used to identify the person. Experiment shows that the performance of the system over 20 subjects is 95.3%.

Keywords

Gabor filters; bioelectric potentials; biometrics (access control); decomposition; electrocardiography; medical signal processing; support vector machines; ECG biometrics identification algorithm; ECG identification; ECG signal decomposition; Gabor dictionary; SVM; cardiac electrical activity; electrocardiogram; matching pursuit; sparse decomposition; support vector machine; Biometrics; Databases; Electrocardiography; Feature extraction; Heart beat; Matching pursuit algorithms; Support vector machines; biometric identification; electrocardiogram; matching pursuit; support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-9351-7

Type

conf

DOI

10.1109/BMEI.2011.6098470

Filename

6098470