Person Identification using Electrocardiograms

In this paper, we demonstrate that the electrocardiogram (ECG) can be used as a biometric. While previous studies have shown the potential of an ECG biometric, this research demonstrates it under conditions that include intra-individual variations and a simple user interface, consisting of electrodes held on the pads of the subject´s thumbs. ECG person identification was accomplished through quantitative comparisons of an unknown signal to enrolled signals. The quantitative comparisons were: the correlation coefficient and a wavelet distance measure. It was found that the combination of these two methods provided improved performance, relative to either individual method. ECG person identification accuracy was 90.8%. While this accuracy is relatively low compared to conventional biometrics, such as fingerprints, the ECG can be used as supplementary information for a multi-modal biometric system. A multi-modal system that includes the ECG would have increased accuracy and robustness, without necessarily requiring any change to the perceived user interface. At minimum, the ECG would be useful in providing liveness detection