The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
ECG Biometric Recognition: A Comparative Analysis
Abstract
The electrocardiogram (ECG) is an emerging biometric modality that has seen about 13 years of development in peer-reviewed literature, and as such deserves a systematic review and discussion of the associated methods and findings. In this paper, we review most of the techniques that have been applied to the use of the electrocardiogram for biometric recognition. In particular, we categorize the methodologies based on the features and the classification schemes. Finally, a comparative analysis of the authentication performance of a few of the ECG biometric systems is presented, using our inhouse database. The comparative study includes the cases where training and testing data come from the same and different sessions (days). The authentication results show that most of the algorithms that have been proposed for ECG-based biometrics perform well when the training and testing data come from the same session. However, when training and testing data come from different sessions, a performance degradation occurs. Multiple training sessions were incorporated to diminish the loss in performance. That notwithstanding, only a few of the proposed ECG recognition algorithms appear to be able to support performance improvement due to multiple training sessions. Only three of these algorithms produced equal error rates (EERs) in the single digits, including an EER of 5.5% using a method proposed by us.
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Cites
Goldberger, A. L., Amaral, L. A. N., Glass, L., Hausdorff, J. M., Ivanov, P. C., Mark, R. G., Mietus, J. E., Moody, G. B., Peng, C.-K., & Stanley, H. E. (2000) · Circulation · doi:10.1161/01.cir.101.23.e215 · Cited by 14,809
The DET curve in assessment of detection task performance
Martin, A., Doddington, G., Kamm, T., Ordowski, M., & Przybocki, M. (1997) · 5th European Conference on Speech Communication and Technology (Eurospeech 1997) · doi:10.21437/eurospeech.1997-504 · Cited by 1,384
ECG analysis: a new approach in human identification
Biel, L., Pettersson, O., Philipson, L., & Wide, P. (2001) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/19.930458 · Cited by 949
Unveiling the Biometric Potential of Finger-Based ECG Signals
Lourenço, A., Silva, H., & Fred, A. (2011) · Computational Intelligence and Neuroscience · doi:10.1155/2011/720971 · Cited by 754
Israel, S. A., Irvine, J. M., Cheng, A., Wiederhold, M. D., & Wiederhold, B. K. (2005) · Pattern Recognition · doi:10.1016/j.patcog.2004.05.014 · Cited by 669
Laguna, P., Mark, R. G., Goldberg, A., & Moody, G. B. (2002) · Computers in Cardiology 1997 · doi:10.1109/cic.1997.648140 · Cited by 606
Wavelet Distance Measure for Person Identification Using Electrocardiograms
Chan, A. D. C., Hamdy, M. M., Badre, A., & Badee, V. (2008) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2007.909996 · Cited by 363
Analysis of Human Electrocardiogram for Biometric Recognition
Wang, Y., Agrafioti, F., Hatzinakos, D., & Plataniotis, K. N. (2007) · EURASIP Journal on Advances in Signal Processing · doi:10.1155/2008/148658 · Cited by 339
Best practices in testing and reporting performance of biometric devices.
Mansfield, A., & Wayman, J. L. (2002) · OpenGrey (Institut de l'Information Scientifique et Technique) · Cited by 325
One-lead ECG for identity verification
Shen, T. W., Tompkins, W. J., & Hu, Y. H. (2003) · Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology · doi:10.1109/iembs.2002.1134388 · Cited by 278
Cited by
Zhang, Q., Zhou, D., & Zeng, X. (2017) · IEEE Access · doi:10.1109/access.2017.2707460 · Cited by 282
Metadata
- Authors
- Odinaka, I., Lai, P.-H., Kaplan, A. D., O'Sullivan, J. A., Sirevaag, E. J., & Rohrbaugh, J. W.
- Venue
- IEEE Transactions on Information Forensics and Security
- Published
- 2012-12
- Volume
- 7
- Issue
- 6
- Pages
- 1812-1824
- ISSN
- 1556-6013 (ISSN-L)
- 1556-6021
- OpenAlex
- W2007123640
- Cited by
- 356
- References
- 43
- FWCI
- 25.23
- Type
- journal article
- Language
- en
- Open access
- closed
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- Odinaka, I., Lai, P.-H., Kaplan, A. D., O'Sullivan, J. A., Sirevaag, E. J., & Rohrbaugh, J. W. (2012). ECG Biometric Recognition: A Comparative Analysis. IEEE Transactions on Information Forensics and Security. https://doi.org/10.1109/tifs.2012.2215324
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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