Journal article Open Access

Person Identification by Using AR Model for EEG Signals

Gelareh Mohammadi; Parisa Shoushtari; Behnam Molaee Ardekani; Mohammad B. Shamsollahi

A direct connection between ElectroEncephaloGram (EEG) and the genetic information of individuals has been investigated by neurophysiologists and psychiatrists since 1960-s; and it opens a new research area in the science. This paper focuses on the person identification based on feature extracted from the EEG which can show a direct connection between EEG and the genetic information of subjects. In this work the full EO EEG signal of healthy individuals are estimated by an autoregressive (AR) model and the AR parameters are extracted as features. Here for feature vector constitution, two methods have been proposed; in the first method the extracted parameters of each channel are used as a feature vector in the classification step which employs a competitive neural network and in the second method a combination of different channel parameters are used as a feature vector. Correct classification scores at the range of 80% to 100% reveal the potential of our approach for person classification/identification and are in agreement to the previous researches showing evidence that the EEG signal carries genetic information. The novelty of this work is in the combination of AR parameters and the network type (competitive network) that we have used. A comparison between the first and the second approach imply preference of the second one.

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  • A. Anoklin, O. Fisher, Y. Mao, P. Vogt, E. Schalt, F. Vogel,(1999), "A genetic study of the human low-voltage electroencephalogram," Human Genetic ,vol. 90,PP. 99-112,1992. [10] M. Poulos, M. Rangoussi, V. Chrissicopoulos, A. Evagelou, " person identification based on parametric processing on the EEG," Processings IEE of the Sixth International Conference on Electronics, Circuits and Systems, ICECS-99, Pafos, Cyprous. September 1999, PP. 283-286. [11] M. Poulos, M. Rangoussi, V. Chrissicopoulos, A. Evagelou, "parametric person identification from the EEG using computational geometry," Processings IEE of the Sixth International Conference on Electronics, Circuits and Systems, ICECS-99, Pafos, Cyprous. September 1999, PP. 1005-1012. [12] N. Hazarika, A. Tsoi, A. Sergejew, "Nonlinear Consideration in EEG signal classification," IEEE Transaction on Signal Processing,vol. 45, No. 4,PP. 829-836,1997. [13] N. Nielsen, B. Harvand, "The electroencephalogram in univular twins brought up apart", Acta Genetica,vol. 8,PP. 57-64,1958. [14] T. Kohonen, "Self-organization and associative memory," 3rd ed., Springer-Verlag, New York, 1988 [15] R. Plomin , "The role of inheritance in behavior," Science, vol. 248, PP. 183-188,1990. [16] W. Lennox, E. Gibbs, F. Gibbs, "The brain-patern, an hereditary trail," The Journal of Heredity, vol. 36, PP. 233-243, 1945. [17] M. Poulos, M. Rangoussi, E. Kafetzopoulos, "Person identification via the EEG using computational geometry algorithms," Proc. Intl. Conf. EUSIPCO-98, Rhodes, Greece, Sept. 1998. [18] H. H. Stassen, G. Bomben, P. Propping, "Genetic aspects of the EEG: an investigation into the withinpair similarity of monozygotic and dizygotic twins with a new method of analysis," Electroencephalography and Clinical Neurophysiology,vol. 66, PP. 489-581, 1987. [19] N.E. Sviderskaya, T.A. Korolkova, "Genetic Features of spatial organization the human cerebral cortex," Neuroscience and Behavioral Physiology, vol. 25, no. 5, 1995. [20] J. Varner, R. Potter, J. Rohrbaugh, "A procedure for automatic classification of EEG genetic variants," Processing of Biological Signals, 30.9-3, Annual International Conference of the IEEE Engineering in Medicine and Biology Society,vol. 13, no. 1,1991. [21] F. Vogel, "The genetic basis of the normal EEG," Human Genetic, vol. 10, PP. 91-114, 1970.
  • A. Kasmia (Neurologist), "Personal Comunication," Oct.2000. Internet
  • A.K.Jain (supervisor), "Biometrics Homepage Michigan State University,".
  • A.Remond(editor) "EEG informatics. A didactic review of methods and applications of EEG data processing," Elsevier Sientific Publishing Inc.,New York,1997.
  • M.Poulos, M.Rangoussi, N.Alexandries, "Neural network based person identification using EEG features," Proceeding IEEE of the international conference on Acoustic , Speech,and Signal Processing, ICASSP-99,Arizona,USA,March 1999,PP. 1117-1120
  • R.Paranjape,J.Mahovsky,L.Benedicenti , "On AR model and other metrics of the EEG for Subject identification," Internet.
  • R.Schmidt , G.Thews " Integrative function of Nervous System," Spriger Verlag,Birlin1983.
  • S.Jain,G.Deshpande, "Parametric Modeling of Brain Signals," Internet.
  • S.Y.Kung, "digital Neural Netwok," (PTR Prentic Hall,Englewood Cliffs,New Jersey 1993)
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