Skip to content


Open Access

Analysis of Human Electrocardiogram for Biometric Recognition

  • Yongjin Wang1Email author,
  • Foteini Agrafioti1,
  • Dimitrios Hatzinakos1 and
  • Konstantinos N. Plataniotis1
EURASIP Journal on Advances in Signal Processing20072008:148658

Received: 3 May 2007

Accepted: 30 August 2007

Published: 19 September 2007


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.


AutocorrelationDiscrete Cosine TransformRecognition AccuracyFull ArticleSecurity Concern

Publisher note

To access the full article, please see PDF.

Authors’ Affiliations

The Edward S. Rogers Sr., Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada


© YongjinWang et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.