Investigation of Human Identification Using Two-Lead Electrocardiogram (ECG) Signals

In this paper, the authors investigate the applicability of Electrocardiogram (ECG) signals for human identification. Wavelet Transform (WT) and Independent Component Analysis (ICA) methods are applied to extract morphological features that appear to offer excellent discrimination among subjects. The proposed method is aimed at the two-lead ECG configuration that is routinely used in long-term continuous monitoring of heart activity. The information from the two ECG leads is fused to achieve improved subject identification.