A.E. Sulavko - Ph.D. (Eng.), Senior Lecturer, Department of Complex Information Security, Omsk State Technical University E-mail: sulavich@mail.ru H.A. Levitskaya - Ph.D. (Eng.), Research Engineer, The Russian Federal Nuclear Center - the All-Russian Research Institute Technical Physics of a n. of the academician E. I. Zababakhin (Snezhinsk) E-mail: Laska_kb@mail.ru A.V. Eremenko - Ph.D. (Eng.), Design Engineer, Research Part, Omsk State Transport University E-mail: nexus-@mail.ru A.E. Samotuga - Post-graduate Student, Omsk State Transport University E-mail: SamotugaSASHOK@mail.ru

Inrecenttime a manufacturing automation and an active implementation of information technologies have been occurred in large industrial enterprises. In spite of this a human mistake rate grows. A working man (e.g. operator, pilot) is under the influence of psychotropic substances or fatigue does not realize that he poses a danger. It may lead to accidents, mistakes or even cause a catastrophe. It is proposed to recognize the psycho-physiological state of the subject by reproduction of the signature in the feature space previously used for the identification of the signers. A database of signatures samples of subjects who are in calm, excited, relaxed, tired states, and a state of light intoxication was formed. Biometric identification features of signature images of a subject are proposed. An assessment of the state identification errors probabilities was conducted based on Bayes formula, the accumulation principle, Euclidean measure, Hamming measure, Pearson metric, Bayes-Pearson metrics and other approaches. In the present article a data that characterize the probability of identification errors of 2,3 and 5 psychophysiological states of signers that participated in the experiment are given.

 

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