- Research Article
- Open access
- Published:
Analysis of Human Electrocardiogram for Biometric Recognition
EURASIP Journal on Advances in Signal Processing volume 2008, Article number: 148658 (2007)
Abstract
Security concerns increase as the technology for falsification advances. There are strong evidences that a difficult to falsify biometric trait, the human heartbeat, can be used for identity recognition. Existing solutions for biometric recognition from electrocardiogram (ECG) signals are based on temporal and amplitude distances between detected fiducial points. Such methods rely heavily on the accuracy of fiducial detection, which is still an open problem due to the difficulty in exact localization of wave boundaries. This paper presents a systematic analysis for human identification from ECG data. A fiducial-detection-based framework that incorporates analytic and appearance attributes is first introduced. The appearance-based approach needs detection of one fiducial point only. Further, to completely relax the detection of fiducial points, a new approach based on autocorrelation (AC) in conjunction with discrete cosine transform (DCT) is proposed. Experimentation demonstrates that the AC/DCT method produces comparable recognition accuracy with the fiducial-detection-based approach.
Publisher note
To access the full article, please see PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
About this article
Cite this article
Wang, Y., Agrafioti, F., Hatzinakos, D. et al. Analysis of Human Electrocardiogram for Biometric Recognition. EURASIP J. Adv. Signal Process. 2008, 148658 (2007). https://doi.org/10.1155/2008/148658
Received:
Accepted:
Published:
DOI: https://doi.org/10.1155/2008/148658