Distance-based Algorithm for Biometric Applications in Meanwaves of Subject’s Heartbeats

Tiago Araújo, Neuza Nunes, Hugo Gamboa, Ana Fred

Abstract

The authors present a new biometric classification procedure based on meanwave’s distances of electrocardiogram (ECG) heartbeats. The ECG data was collected from 63 subjects during two data-recording sessions separated by six months (Time Instance 1, T1, and Time Instance 2, T2). Two classification tests were performed with the goal of subject identification using a distance-based method with the heartbeat waves. In both tests, the enrollment template was composed by the averaging of the T1 waves for each subject. For the first test, we composed five meanwaves of different T1 waves; In the second test, five meanwaves of different groups of T2 waves were composed. Classification was performed through the implementation of a kNN classifier, using the meanwave’s Euclidean distances as features for subject identification. In the first test, with only T1 waves, 95.2% of accuracy was achieved. In the second test, using T2 waves to compose the dataset for testing, the accuracy was 90.5%. The T2 waves belonged to the same subjects but were acquired in different time instances, simulating a real biometric identification problem. We therefore conclude that a distance-based method using meanwaves of ECG heartbeats for each subject is a valid parameter for classification in biometric applications.

References

  1. Chan, A., Hamdy, M., Badre, A., and Badee, V. (2008). Wavelet distance measure for person identification using electrocardiograms. In IEEE Transactions on Instrumentation and Measuremen.
  2. Coutinho, D., Fred, A., and Figueiredo, M. (2010). Personal identification and authentication based on onelead ecg using ziv-merhav cross parsing. In 10th International Workshop on Pattern Recognition in Information Systems.
  3. Jain, A., Hong, L., and Pankanti, S. (2000). Biometric Identification. Communications of the ACM.
  4. Li, M. and Narayanan, S. (2010). Robust ecg biometrics by fusing temporal and cepstral information,. In 20th International Conference on Pattern Recognition.
  5. Lourenco, A., Silva, H., and Fred, A. (2011). Unveiling the biometric potential of finger-based ecg signals. In Computational Intelligence and Neuroscience.
  6. Nunes, N., Araujo, T., and Gamboa, H. (2012). Time Series Clustering Algorithm for Two-Modes Cyclic Biosignals. A. Fred, J. Filipe, and H. Gamboa (Eds.): BIOSTEC 2011, CCIS 273, pp. 233-245. Springer, Heidelberg.
  7. Orange (2012). http://orange.biolab.si/.
  8. Plataniotis, K., Hatzinakos, D., and Lee, J. (2006). Ecg biometric recognition without fiducial detection. In Biometric Consortium Conference, 2006 Biometrics Symposium.
  9. Silva, H., Gamboa, H., and Fred, A. (2007). Applicability of lead v2 ecg measurements in biometrics. In Proceedings of Med-e-Tel.
Download


Paper Citation


in Harvard Style

Araújo T., Nunes N., Gamboa H. and Fred A. (2013). Distance-based Algorithm for Biometric Applications in Meanwaves of Subject’s Heartbeats . In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: BTSA, (ICPRAM 2013) ISBN 978-989-8565-41-9, pages 630-634. DOI: 10.5220/0004358106300634


in Bibtex Style

@conference{btsa13,
author={Tiago Araújo and Neuza Nunes and Hugo Gamboa and Ana Fred},
title={Distance-based Algorithm for Biometric Applications in Meanwaves of Subject’s Heartbeats},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: BTSA, (ICPRAM 2013)},
year={2013},
pages={630-634},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004358106300634},
isbn={978-989-8565-41-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: BTSA, (ICPRAM 2013)
TI - Distance-based Algorithm for Biometric Applications in Meanwaves of Subject’s Heartbeats
SN - 978-989-8565-41-9
AU - Araújo T.
AU - Nunes N.
AU - Gamboa H.
AU - Fred A.
PY - 2013
SP - 630
EP - 634
DO - 10.5220/0004358106300634