A New Approach to ECG Biometric Systems: A Comparitive Study between LPC and WPD Systems

Authors: Justin Leo Cheang Loong, Khazaimatol S Subari, Rosli Besar, Muhammad Kamil Abdullah

Abstract:

In this paper, a novel method for a biometric system based on the ECG signal is proposed, using spectral coefficients computed through linear predictive coding (LPC). ECG biometric systems have traditionally incorporated characteristics of fiducial points of the ECG signal as the feature set. These systems have been shown to contain loopholes and thus a non-fiducial system allows for tighter security. In the proposed system, incorporating non-fiducial features from the LPC spectrum produced a segment and subject recognition rate of 99.52% and 100% respectively. The recognition rates outperformed the biometric system that is based on the wavelet packet decomposition (WPD) algorithm in terms of recognition rates and computation time. This allows for LPC to be used in a practical ECG biometric system that requires fast, stringent and accurate recognition.

Keywords: biometric, ecg, linear predictive coding, wavelet packet decomposition

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1072988

References:

[1] F. Agrafioti and D. Hatzinakos. Fusion of ECG sources for human identification. In 3rd International Symposium on Communications, Control and Signal Processing, pages 1542 - 1547, St. Julians, Malta, 2008.
[2] L. Biel, O. Pettersson, L. Philipson, and P. Wide. ECG analysis: a new approach in human identification. In Proceedings of the 16th IEEE Instrumentation and Measurement Technology Conference, volume 1, pages 557 -561, Venice, Italy, 1999.
[3] L. Biel, O. Pettersson, L. Philipson, and P. Wide. ECG analysis: a new approach in human identification. IEEE Transactions on Instrumentation and Measurement, 50(3):808 - 812, 2001.
[4] O. Boumbarov, Y. Velchev, and S. Sokolov. ECG personal identification in subspaces using radial basis neural networks. In IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, pages 446 - 451, Rende, Italy, 2009.
[5] A. D. C. Chan, M. M. Hamdy, A. Badre, and V. Badee. Person identification using electrocardiograms. In Canadian Conference on Electrical and Computer Engineering, pages 1 - 4, Ottawa, Canada, 2006.
[6] C.-C. Chiu, C.-M. Chuang, and C.-Y. Hsu. A novel personal identity verification approach using a discrete wavelet transform of the ECG signal. In International Conference on Multimedia and Ubiquitous Engineering, pages 201 - 206, Busan, Korea, 2008.
[7] B. A. Eisenstein and R. J. Vaccaro. Feature extraction by system identification. IEEE Transactions on Systems, Man and Cybernetics, 12(1):42 - 50, 1982.
[8] Y. Gahi, M. Lamrani, A. Zoglat, M. Guennoun, B. Kapralos, and K. El- Khatib. Biometric identification system based on electrocardiogram data. In New Technologies, Mobility and Security, pages 1 - 5, Tangier, Morocco, 2008.
[9] M. Guennoun, N. Abbad, J. Talom, S. M. M. Rahman, and K. El-Khatib. Continuous authentication by electrocardiogram data. In IEEE Toronto International Conference Science and Technology for Humanity, pages 40 - 42, Toronto, Canada, 2009.
[10] I. Khalil and F. Sufi. Legendre polynomials based biometric authentication using QRS complex of ECG. In International Conference on Intelligent Sensors, Sensor Networks and Information Processing, pages 297 - 302, Sydney, Australia, 2008.
[11] K.-S. Kim, T.-H. Yoon, J.-W. Lee, D.-J. Kim, and H.-S. Koo. A robust human identification by normalized time-domain features of electrocardiogram. In 27th Annual International Conference of the Engineering in Medicine and Biology Society, pages 1114 - 117, Shanghai, China, 2005.
[12] M. Kyoso. A technique for avoiding false acceptance in ECG identification. In IEEE Engineering in Medicine and Biology Society Asian-Pacific Conference on Biomedical Engineering, pages 190 - 191, the border of Kyoto-Osaka-Nara, Japan, 2003.
[13] M. Kyoso and A. Uchiyama. Development of an ECG identification system. In Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, volume 4, pages 3721 - 3723, Istanbul, Turkey, 2001.
[14] R. Palaniappan and S. Krishnan. Identifying individuals using ECG beats. In International Conference on Signal Processing and Communications, pages 569 - 572, Bangalore, India, 2004.
[15] K. Plataniotis, D. Hatzinakos, and J. Lee. ECG biometric recognition without fiducial detection. In Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference, pages 1 - 6, Baltimore, MD, 2006.
[16] S. Saechia, J. Koseeyaporn, and P. Wardkein. Human identification system based ECG signal. In IEEE TENCON, pages 1 - 4, Hong Kong, China, 2005.
[17] T. Shen, W. Tompkins, and Y. Hu. One-lead ECG for identity verification. In Proceedings of the Second Joint Engineering in Medicine and Biology Society and Biomedical Engineering Society Conference, volume 1, pages 62 - 63, Houstan, TX, 2002.
[18] Y. Singh and P. Gupta. ECG to individual identification. In 2nd IEEE International Conference on Biometrics: Theory, Applications and Systems, pages 1 - 8, Washington, DC, 2008.
[19] J. C. Sriram, M. Shin, T. Choudhury, and D. Kotz. Activity-aware ECGbased patient authentication for remote health monitoring. In Proceedings of the 2009 International Conference on Multimodal Interfaces, pages 297 - 304, Cambridge, MA, 2009.
[20] W. Ting, Y. Guo-zheng, Y. Bang-hua, and S. Hong. EEG feature extraction based on wavelet packet decomposition for brain computer interface. Measurement, 41(6):618 - 625, 2008.
[21] Y.-T. Tsao, T.-W. Shen, T.-F. Ko, and T.-H. Lin. The morphology of the electrocardiogram for evaluating ECG biometrics. In 9th International Conference on e-Health Networking, Application and Services, pages 233 - 235, Taipei, Taiwan, 2007.
[22] Y. Wang, K. Plataniotis, and D. Hatzinakos. Integrating analytic and appearance attributes for human identification from ECG signals. In Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference, pages 1 - 6, Baltimore, MD, 2006.
[23] J. Yao and Y. Wan. A wavelet method for biometric identification using wearable ECG sensors. In 5th International Summer School and Symposium on Medical Devices and Biosensors, pages 297 - 300, Hong Kong, China, 2008.
[24] Z. Zhang and D. Wei. A new ECG identification method using Bayes- theorem. In IEEE TENCON, pages 1 - 4, Hong Kong, China, 2006.