Statistical Analysis for Human Authentication Using ECG Waves

  • Chetana Hegde
  • H. Rahul Prabhu
  • D. S. Sagar
  • P. Deepa Shenoy
  • K. R. Venugopal
  • L. M. Patnaik
Part of the Communications in Computer and Information Science book series (CCIS, volume 141)


Automated security is one of the major concerns of modern times. Secure and reliable authentication of a person is in great demand. A biometric trait like the electrocardiogram (ECG) of a person is unique and secure. In this paper we propose an authentication system based on ECG by using statistical features like mean and variance of ECG waves. Statistical tests like Z −test, t −test and χ 2 −tests are used for checking the authenticity of an individual. Then confusion matrix is generated to find False Acceptance Ratio (FAR) and False Rejection Ratio (FRR). This methodology of authentication is tested on data set of 200 waves prepared from ECG samples of 40 individuals taken from Physionet QT Database. The proposed authentication system is found to have FAR of about 2.56% and FRR of about 0.13%. The overall accuracy of the system is found to be 99.81%.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Jain, A.K., Ross, A., Prabhakar, S.: An Introduction to Biometric Recognition. IEEE Trans. on Circuits Sys. 14(1), 4–20 (2004)Google Scholar
  2. 2.
    Boles, W., Chu, S.: Personal Identification using Images of the Human Palm. In: Proc. IEEE TENCON Conf. (1997)Google Scholar
  3. 3.
    Hegde, C., Manu, S., Shenoy, P.D., Venugopal, K.R., Patnaik, L.M.: Secure Authentication using Image Processing and Visual Cryptography for Banking Applications. In: Proc. Int. Conf. on Advanced Computing (ADCOM 2008), pp. 65–72 (2008)Google Scholar
  4. 4.
    Boles, W.: A Security System based on Human Iris Identification using Wavelet Transforms. In: Proc. First Int. Conf. Knowledge-Based Intelligent Electron. Syst. (1997)Google Scholar
  5. 5.
    Samal, A., Iyengar, P.: Automatic Recognition and Analysis of Human Faces and Facial Expressions: A Survey. Pattern Recognition 25(1), 65–77 (1992)CrossRefGoogle Scholar
  6. 6.
    Hegde, C., Srinath, U.S., Aravind Kumar, R., Rashmi, D.R., Sathish, S., Shenoy, P.D., Venugopal, K.R., Patnaik, L.M.: Ear Pattern Recognition using Centroids and Cross-Points for Robust Authentication. In: Proc. Second Int. Conf. on Intelligent Human and Computer Interaction (IHCI 2010), pp. 378–384 (2010)Google Scholar
  7. 7.
    Dumn, D.: Using a Multi-layer Perceptron Neural for Human Voice Identification. In: Proc. Fourth Int. Conf. Signal Process. Applicat. Technol. (1993)Google Scholar
  8. 8.
    Hegde, C., Rahul Prabhu, H., Sagar, D.S., Vishnu Prasad, K., Shenoy, P.D., Venugopal, K.R., Patnaik, L.M.: Authentication of Damaged Hand Vein Patterns by Modularization. In: IEEE TENCON (2009)Google Scholar
  9. 9.
    Simon, B.P., Eswaran, C.: An ECG Classifier Designed using Modified Decision Based Neural Network. Computers and Biomedical Research 30, 257–272 (1997)CrossRefGoogle Scholar
  10. 10.
    Biel, L., Pettersson, O., Philipson, L., Wide, P.: ECG Analysis: A New Approach in Human Identification. IEEE Trans. on Instrumentation and Measurement 50(3), 808–812 (2001)CrossRefGoogle Scholar
  11. 11.
    Rijnbeek, P.R., Witsenburg, M., Schrama, E., Hess, J., Kors, J.A.: New Normal Limits for the Pediatric Electrocardiogram. European Heart Journal 22, 702–711 (1985)CrossRefGoogle Scholar
  12. 12.
    Esbensen, K., Schonkopf, S., Midtgaard, T.: Multivariate Analysis in Practice, 1st edn., vol. 1 (1994)Google Scholar
  13. 13.
    Shen, T.W., Tompkins, W.J., Hu, Y.H.: One-Lead ECG for Identity Verification. In: Proc. of Second Joint Conf. of IEEE EMBS/BMES, pp. 62–63 (2002)Google Scholar
  14. 14.
    Kung, S.Y., Taur, J.S.: Decision-based Neural Networks with Signal/Image Classification Applications. IEEE Trans. on Neural Networks 6(1), 170–181 (1995)CrossRefGoogle Scholar
  15. 15.
    Pan, J., Tompkins, W.J.: A Real Time QRS Detection Algorithm. IEEE Trans. on Biomedical Engineering 33(3), 230–236 (1985)CrossRefGoogle Scholar
  16. 16.
    Singh, Y.N., Gupta, P.: Biometrics method for human identification using electrocardiogram. In: Tistarelli, M., Nixon, M.S. (eds.) ICB 2009. LNCS, vol. 5558, pp. 1270–1279. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  17. 17.
    Laguna, P., Mark, R.G., Goldberger, A.L., Moody, G.B.: A Database for Evaluation of Algorithms for Measurement of QT and Other Waveform Intervals in the ECG Computers in Cardiology, pp. 673–676 (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Chetana Hegde
    • 1
  • H. Rahul Prabhu
    • 2
  • D. S. Sagar
    • 2
  • P. Deepa Shenoy
    • 2
  • K. R. Venugopal
    • 2
  • L. M. Patnaik
    • 3
  1. 1.Bangalore UniversityBangaloreIndia
  2. 2.Department of CSE, UVCEBangalore UniversityBangalore
  3. 3.DIATPuneIndia

Personalised recommendations