Abstract
In this paper, we present a new segmented based method for human identification using Frechet distances and the characteristics of the lag-feature matrices of six fiducial based QRS features. We examined the applicability of our methodology on 124 ECG records of 62 subjects from the publicly available ECG ID data base. Our experiments show that the Frechet distance can identify majority of the subjects (44 individuals) using the feature matrix of QRS segment lagged by one beat with an identification accuracy ranging from 80% to 100%. Our preliminary results indicate that identifying humans using segmented approaches can be potentially useful.