HeartCode: A novel binary ECG-based template

Abstract

Recent studies on ECG signals proved that they can be employed as biometric traits able to obtain sufficient accuracy in a wide set of applicative scenarios. Most of the systems in the literature, however, are based on templates consisting in vectors of integer or floating point numbers. While any numerical representation is inherently binary, in here we consider as binary templates only those codings in which similarity or distance metrics can be directly applied to the for performing identity comparisons. With respect to templates composed by integer or floating point values, the use of binary templates presents important advantages, such as smaller memory space, and faster and simpler matching functions. Binary templates could therefore be adopted in a wider range of applications with respect to traditional ECG templates, like wearable devices and body area networks. Moreover, binary templates are suitable for most of the biometric template protection methods in the literature. This paper presents a novel approach for computing and processing binary ECG templates (HeartCode). Experimental results proved that the proposed approach is effective and obtains performance comparable to more mature biometric methods for ECG recognition, obtaining Equal Error Rate (EER) of 8.58% on a significantly large database of 8400 samples extracted from Holter acquisitions performed in uncontrolled conditions.