Name
Abstract | ||
|---|---|---|
Research over the past decade has demonstrated the capability of the electrocardiographic (ECG) signal to be used as a biometric trait, through which the identity of an individual can be recognized. Given its universality, intrinsic aliveness detection, continuous availability, and inherent hidden nature, the ECG is an interesting biometric modality enabling the development of novel applications, where non-intrusive and continuous authentication are critical factors. Examples include personal computers, the gaming industry, and the auto industry, especially for car sharing programs and fleet management solutions. Nonetheless, from a theoretical point of view, there are still some challenges to overcome in bringing ECG biometrics to mass markets. In particular, the issues of uniqueness (related to inter-subject variability) and permanence (related to intra-subject variability) are still largely unanswered. This work focuses on the uniqueness issue, evaluating the performance of our ECG biometric system over a database encompassing 618 subjects. Additionally, we performed tests with subsets of this population. The results cement the ECG as a viable trait to be used for identity recognition, having obtained and Equal Error Rate of 9.01% and an Error of Identification of 15.64% for the entire test population. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-26453-0_7 | Lecture Notes in Electrical Engineering |
Keywords | DocType | Volume |
Biometrics,Person recognition,ECG,Classification | Conference | 370 |
ISSN | Citations | PageRank |
1876-1100 | 0 | 0.34 |
References | Authors | |
8 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlos Carreiras | 1 | 41 | 6.96 |
| André Lourenço | 2 | 312 | 45.33 |
| Hugo Silva | 3 | 12 | 3.49 |
| Ana L. N. Fred | 4 | 1317 | 195.30 |
| Rui Ferreira | 5 | 0 | 0.34 |