Analysis of Human Electrocardiogram for Biometric Recognition. (12th November 2007)

• Record Type: Journal Article
• Authors: Wang Wang, Yongjin Yongjin; Agrafioti Agrafioti, Foteini Foteini; Hatzinakos Hatzinakos, Dimitrios Dimitrios; Plataniotis Plataniotis, Konstantinos N. Konstantinos N.
• Other Names: Ross Ross Arun Arun Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2007-11-12
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/148658
• Languages: English
• ISSNs: 1687-6172

Abstract

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.