Activity-aware ECG-based patient authentication for remote health monitoring
Proceedings of the 2009 international conference on Multimodal interfaces
Study of human identification by electrocardiogram waveform morph
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Evaluating the use of ECG signal in low frequencies as a biometry
Expert Systems with Applications: An International Journal
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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.