A Wavelet-based Approach to Electrocardiogram (ECG) and Phonocardiogram (PCG) Subject Recognition

This thesis studies the applicability of two cardiac traits, the electrocardiogram (ECG) and the phonocardiogram (PCG), as biometrics. There is strong evidence that cardiac electrical activity (ECG) embeds highly distinctive characteristics, suitable for applications such as the recognition of human subjects. On the other hand, having the same origin with the ECG signal, it is believed that the PCG signal conveys distinctive information of an individual which can be deployed in biometric applications. Such recognition systems traditionally provide two modes of functionality, identification and authentication; frameworks for subject recognition are herein proposed and analyzed in both scenarios. Moreover, the expression of the cardiac signals is subject to alternation with heart rate and noise components. Thus, the central consideration of this thesis is the design and evaluation of robust recognition approaches that can compensate for these effects. A recognition system based on each, the ECG and the PCG, is developed and evaluated. Furthermore, a fusion of the two signals in a multimodal biometric system is investigated.MAS