I.M. Mazikin¹
Dr. Med., Professor M.M. Lapkin¹
Dr. Med., Professor R.A. Zorin¹
Dr. Med., Professor A.L. Pokhachevsky^{1, 2}
PhD, Associate Professor M.V. Akulina^1
1I.P. Pavlov Ryazan State Medical University, Ryazan
²I.M. Sechenov First Moscow State Medical University, Moscow

Objective of the study was to identify significant physiological mechanisms of performance formation when passing control standards in physical culture and to establish the relationship between performance indicators and individual psychophysiological characteristics.
Methods and structure of the study. 120 young men aged 18-20 years old belonging to the main health group were examined. With the help of cluster analysis, groups were identified with different performance in passing control standards in terms of speed endurance and speed-strength indicators. To solve the problem of classifying students, taking into account their psychophysiological characteristics, an artificial neural network (ANN) was created, distributing students into groups with specified characteristics.
Results and conclusions. When analyzing the motivational basis of behavior, it was revealed that the students of the first cluster were dominated by an internal motive and the motive of focusing on success, with at the same time high rates of assessing their potential. The students of the second cluster were dominated by the motive for assessing the significance of the result of activity. Statistically significant differences in personal psychophysiological characteristics and indicators of physical performance were established in the subjects of the identified clusters. On the basis of a set of data obtained, cluster analysis and ANN technology made it possible to predict the performance of students with a high probability, as well as to rank indicators according to their significance for the formation of unequal performance.

Keywords: psychophysiological characteristics, cluster analysis, artificial neural networks.

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