A Novel Personal Identity Verification Approach Using a Discrete Wavelet Transform of the ECG Signal

Abstract

The purpose of this research is to develop a real time system for individual verification with the electrocardiogram (ECG) signal. The ECG signal varies from person to person and it can be used as a new biometric for individual verification. The discrete wavelet transform extract signal features by wavelet coefficients of one-lead ECG signal. Using the proposed approach on 35 normal subjects and 10 arrhythmia patients, 100% verification rate was obtained for normal subjects and 81% verification rate for arrhythmia patients. Furthermore, the performance of the ECG verification system was evaluated by the false acceptance rate (FAR) and false rejection rate (FRR). The FAR was 0.83% and FRR was 0.86%for a database containing only 35 normal subjects. When 10 arrhythmia patients were added into the database, the FAR became 12.50% and the FRR 5.11%. The experimental results demonstrate that the proposed system works very well for normal subjects.