Artificial Neural Networks for Evaluation of Psychophysiological State

Abstract

In this document, we make an analysis of the possibility of using neural networks in the development of tests to evaluate the psychophysiological state of a human. Also, in this paper, the developed system of psychophysiological diagnostics is presented. This system will automate the execution and processing of results of the express testing methods for evaluation the psychophysiological state. The described model of evaluation the human’s psychophysiological state using a neural network has the following advantages: remote diagnostics, stability and accuracy of the results, the ability to self-training by detecting complex dependencies, identification of typical trends for people of a certain profession or in a particular area. It has been proved that the usage of neural networks for processing the results of psychophysiological tests will improve the accuracy of diagnosis.