О.V. Shatalova - Ph.D. (Eng.), Associate Professor, Southwest State University
S.E. Surzhikova - Post-graduate Student, Southwest State University
A.S. Bogdanov - Post-graduate Student, Southwest State University

The problems of research of anomalous zones of conductivity of bioactive points (BATH) are described and the ways of researches, sent to perfection and increase of diagnostic efficiency, offer. It is set that diagnostic efficiency offered approach can be enhanceable due to the increase of volume of the information taken off with separate BATH, with the subsequent use of different combinations of methods of treatment of the got information and neural-net models. CAS is worked out, including the DAU connected to the personal computer, intercoupler with an object and corresponding software. To the article the functional diagram of the worked out CAS is driven for research of voltage-current characteristics BATH. The basic modules included in devices are described. The modes of strengthening of output tension are set, optimal descriptions are certain. At a design the different forms of excitant tension are investigational for forming of voltage-current characteristics of biomaterial. The examples of epure of the investigated tensions are shown. The parameters of excitant tension are set and certain. Shown on the example of research of voltage-current characteristics BATH of meridian of heart of C7 for twenty volunteers. Determination of optimal dimension of space of informing signs is executed on the basis of factor analysis, the optimal size of informing signs is set. It is set that for classification of biomaterial it is expedient to apply the multiagent systems classifiers based on probabilistic neural networks and unclear neural networks. Classifiers contain three macrolayers, first from that consists of the modules of the probabilistic three-layered neural networks, second and third macrolayer - from the modules of double-layer unclear neural networks, thus the amount of the modules in macrolayers is equal to the number of differentiable classes of diseases. Classifiers allow to define subjective probabilities of belonging of entrance vector to the distinguished classes.