Medical biometrics: The perils of ignoring time dependency

The electrocardiogram (ECG) is a medical signal that has lately drawn interest from the biometrics community, and has been shown to have significantly discriminative characteristics in a population. This paper brings to light the particular challenges of electrocardiogram recognition to advocate that time dependency is a controversial point. In contrast to traditional biometrics, ECG allows for continuous authentication and consequently expands the range of applications. However, time varying biometrics put on the line the recognition accuracy due to increased intra subject variability. This paper suggests a novel framework for bypassing this inadequacy. A template update methodology is proposed and demonstrated to boost the recognition performance over 2 hour recordings of 10 subjects.