The Transactions of the Korean Institute of Electrical Engineers P (전기학회논문지P)

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지
DOI QR코드

DOI QR Code

ECG based Personal Authentication using Principal Component Analysis

주성분 분석기법을 이용한 심전도 기반 개인인증

  • Cho, Ju-Hee (School of Electronics Engineering, Chungbuk National University) ;
  • Cho, Byeong-Jun (School of Electronics Engineering, Chungbuk National University) ;
  • Lee, Dae-Jong (School of Electronics Engineering, Chungbuk National University) ;
  • Chun, Myung-Geun (School of Electronics Engineering, Chungbuk National University)
  • Received : 2017.11.06
  • Accepted : 2017.11.24
  • Published : 2017.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

The PCA(Principal Component Analysis) algorithm is widely used as a technique of expressing the eigenvectors of the covariance matrix that best represents the characteristics of the data and reducing the high dimensional vector to a low dimensional vector. In this paper, we have developed a personal authentication method based on ECG using principal component analysis. The proposed method showed excellent recognition performance of 98.2 [%] when it was experimented using electrocardiogram data obtained at weekly intervals. Therefore, it can be seen that it is useful for personal authentication by reducing the dimension without changing the information on the variability and the correlation set variable existing in the electrocardiogram data by using the principal component analysis technique.

Keywords

References

  1. A. Kaul, A. S. Arora and S. Chauhan, "ECG based human authentication using synthetic ECG template," In Signal Processing, Computing and Control (ISPCC), 2012 IEEE International Conference on, pp. 1-4, 2012.
  2. Fang, Shih-Chin, and Hsiao-Lung Chan, "Human identification by quantifying similarity and dissimilarity in electrocardiogram phase space," Pattern Recognition, vol. 42, no. 9, pp. 1824-1831, 2009. https://doi.org/10.1016/j.patcog.2008.11.020
  3. Biel, Lena, et al., "ECG analysis: a new approach in human identification," IEEE Transactions on Instrumentation and Measurement, vol. 50, no. 3, pp. 808-812, 2001. https://doi.org/10.1109/19.930458
  4. T. W. Shen, W. J. Tompkins, Y. H. Hu, "One-lead ECG for Identity Verification," in Proceedings of the 2nd Joint Engineering in Medicine and Biology, 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society (EMBS/BMES), vol. 1, pp. 62-63, 2002.
  5. M. Kyoso, and A. Uchiyama, "Development of an ECG identification system," in Proceedings of the 23rd Annual International Conference of the IEEE on Engineering in Medicine and Biology Society, vol. 4, pp. 3721-3723, 2001.
  6. Plataniotis, Konstantinos N., Dimitrios Hatzinakos, and Jimmy KM Lee, "ECG biometric recognition without fiducial detection," Biometric Consortium Conference, 2006 Biometrics Symposium: Special Session on Research at the. IEEE, pp. 1-6, 2006.
  7. Chiu, Chuang-Chien, Chou-Min Chuang, and Chih-Yu Hsu, "A novel personal identity verification approach using a discrete wavelet transform of the ECG signal," Multimedia and Ubiquitous Engineering, 2008. MUE 2008. International Conference on. IEEE, pp. 201-206, 2008.
  8. Li, Ming, and Shrikanth Narayanan, "Robust ECG biometrics by fusing temporal and cepstral information," Pattern recognition (icpr), 2010 20th international conference on, IEEE, pp. 1326-2329, 2010.
  9. S. I. Safie, J. J. Soraghan, and L. Petropoulakis, "Electrocardiogram biometric authentication using pulse active ratio (PAR)," IEEE Trans. on Inf. Forensics and Security, vol. 6, no. 4, pp. 1315-1322, 2011. https://doi.org/10.1109/TIFS.2011.2162408