A Key to Your Heart: Biometric Authentication Based on ECG Signals
This addresses user authentication for security applications, but it is incremental as it applies an existing method to new data.
The paper tackled biometric authentication using ECG signals from a consumer-grade monitor, achieving error rates of 2.4% within one session and 9.7% across sessions over 4 months.
In recent years, there has been a shift of interest towards the field of biometric authentication, which proves the identity of the user using their biological characteristics. We explore a novel biometric based on the electrical activity of the human heart in the form of electrocardiogram (ECG) signals. In order to explore the stability of ECG as a biometric, we collect data from 55 participants over two sessions with a period of 4 months in between. We also use a consumer-grade ECG monitor that is more affordable and usable than a medical-grade counterpart. Using a standard approach to evaluate our classifier, we obtain error rates of 2.4% for data collected within one session and 9.7% for data collected across two sessions. The experimental results suggest that ECG signals collected using a consumer-grade monitor can be successfully used for user authentication.