Title :
A novel human identification system based on electrocardiogram features
Author :
Gurkan, Hakan ; Guz, Umit ; Yarman, B.S.
Author_Institution :
Dept. of Electr. & Electron. Eng., Isik Univ., Istanbul, Turkey
Abstract :
In this work we present a novel biometric authentication approach based on combination of AC/DCT features, MFCC features, and QRS beat information of the ECG signals. The proposed approach is tested on a subset of 30 subjects selected from the PTB database. This subset consists of 13 healthy and 17 non-healthy subjects who have two ECG records. The proposed biometric authentication approach achieves average frame recognition rate of %97.31 on the selected subset. Our experimental results imply that the frame recognition rate of the proposed authentication approach is better than that of ACDCT and MFCC based biometric authentication systems, individually.
Keywords :
bioelectric potentials; cryptographic protocols; electrocardiography; feature extraction; medical signal detection; medical signal processing; AC-DCT feature extraction; ACDCT based biometric authentication system; ECG signal; MFCC based biometric authentication system; MFCC feature extraction; PTB database; QRS beat information; average frame recognition rate; biometric authentication approach; electrocardiogram feature extraction; human identification system; Authentication; Band-pass filters; Databases; Discrete cosine transforms; Electrocardiography; Feature extraction; Mel frequency cepstral coefficient; ECG; feature extraction; human identification;
Conference_Titel :
Signals, Circuits and Systems (ISSCS), 2013 International Symposium on
Conference_Location :
Iasi
Print_ISBN :
978-1-4799-3193-4
DOI :
10.1109/ISSCS.2013.6651266
