A Sequential Procedure for Individual Identity Verification Using ECG

The electrocardiogram (ECG) is an emerging novel biometric for human identification. One challenge for the practical use of ECG as a biometric is minimizing the time needed to acquire user data. We present a methodology for identity verification that quantifies the minimum number of heartbeats required to authenticate an enrolled individual. The approach rests on the statistical theory of sequential procedures. The procedure extracts fiducial features from each heartbeat to compute the test statistics. Sampling of heartbeats continues until a decision is reached—either verifying that the acquired ECG matches the stored credentials of the individual or that the ECG clearly does not match the stored credentials for the declared identity. We present the mathematical formulation of the sequential procedure and illustrate the performance with measured data. The initial test was performed on a limited population, twenty-nine individuals. The sequential procedure arrives at the correct decision in fifteen heartbeats or fewer in all but one instance and in most cases the decision is reached with half as many heartbeats. Analysis of an additional 75 subjects measured under different conditions indicates similar performance. Issues of generalizing beyond the laboratory setting are discussed and several avenues for future investigation are identified.