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Unveiling the Biometric Potential of Finger-Based ECG Signals
Joint Authors
Fred, Ana
Lourenço, André
Silva, Hugo
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-08-07
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
The ECG signal has been shown to contain relevant information for human identification.
Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest.
In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin.
The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem.
Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization.
Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.
American Psychological Association (APA)
Lourenço, André& Silva, Hugo& Fred, Ana. 2011. Unveiling the Biometric Potential of Finger-Based ECG Signals. Computational Intelligence and Neuroscience،Vol. 2011, no. 2011, pp.1-8.
https://search.emarefa.net/detail/BIM-493298
Modern Language Association (MLA)
Lourenço, André…[et al.]. Unveiling the Biometric Potential of Finger-Based ECG Signals. Computational Intelligence and Neuroscience No. 2011 (2011), pp.1-8.
https://search.emarefa.net/detail/BIM-493298
American Medical Association (AMA)
Lourenço, André& Silva, Hugo& Fred, Ana. Unveiling the Biometric Potential of Finger-Based ECG Signals. Computational Intelligence and Neuroscience. 2011. Vol. 2011, no. 2011, pp.1-8.
https://search.emarefa.net/detail/BIM-493298
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-493298