MATHEMATICAL AND SOFTWARE TOOLS TO DETECT THE FUNCTIONAL STATE OF HUMAN ON THE BASIS OF NEURAL-NETWORK APPROACH
This paper deals with the matters of detecting the functional state of human ebriety. The conventional methods of diagnosing the ebriety states are described. The special aspects of human pupillary responses to changing illuminating intensity are analyzed, including those considering functional deviations. To analyze pupillary responses, the method of pupillometry is proposed to be used. We compare the classical methods of analyzing the pupillograms with the data mining methods. The conclusion is that it is necessary to assess the values of pupillogram values, based on the neural-network approach. The task is to develop mathematical and software tools for detecting the functional state of human ebriety by his or her pupillary response to pulse light stimulus. This task is solved using the neural-network approach based on the collective of neural networks to be formed using the bootstrapping method. The methods are proposed for collecting and pre-processing the initial data for analysis, for building a neural-network model of detecting the functional state of human ebriety, as well as the method and algorithm of optimizing the composition of inputs and the number of hidden neurons of the underlying neural networks. ROC analysis is used to search for the optimal cutoff point for the classes of solutions formed at the outputs of neural-network models. We present the description of a reduced neural-network model and of the software complex developed. Its purpose, development tool, structure, composition, and functioning example are described. To assess the efficiency of mathematical tools, we provide the findings obtained in our studies conducted based on the software complex, as well as the results of comparing the accuracy of the neural-network model with the accuracies of other classification methods. For the validation purposes, we solve the task of detecting the functional state of human ebriety in attending a pre-trip medical examination. A human functional state detection schema is proposed. To enhance the efficiency of the pre-trip medical examination procedures, we justify the topicality of using in them the software developed. We describe the pre-trip medical examination schema using the decision support system. The efficiency of detecting the functional state of human ebriety is analyzed. The conclusion is made that procurement and time costs are reduced if the pre-trip medical examination is performed using the approach proposed and that this approach can be efficiently used in other applications.