Dr.Med. M.M. Lapkin²
Dr.Med A.L. Pokhachevsky^{1, 2}
I.M. Mazikin²
A.V. Fomichev^3
1I.M. Sechenov First Moscow Institute of Medicine, Moscow
² Ryazan State Medical University of the Ministry of Health of Russia, Ryazan
³Vologda Institute of Law and Economics of the Federal Penitentiary Service of Russia of Russia, Vologda

Keywords: maximal exercise testing, mathematical modeling of time series of cardiorhythmography.

Introduction. Equal levels of physical performance, athletes are shown in load testing, to assess the impact of their personal qualities, but the use of mathematical modeling native cardiorhythmography opens early, more subtle and profound markers of endurance exercise, which not only show individual differences in performance, but also allow to detect relationships, the influence of personality traits of athletes.
The purpose of the study is to identify the relationship of personal qualities of athletes with markers of physical activity tolerance.
Methodology and organization of the study. Maximum Bicycle ergometric testing was performed using an individual Protocol [1]. The CRG of the early adaptation period was subjected to mathematical modeling of the time series (BP). The time series of CRG 1, 2, and 3 min of the loading period were analyzed as linear (Y=aX+b) and hyperbolic (Y=a/X+b) mathematical models, the markers of which (a, b) were used to determine the level of endurance and fitness.
The study of personal and situational anxiety was carried out by the Taylor and spielberger tests; the type of behavior, focus on performance – by the Jenkins tests; the levels of ergicity, plasticity, tempo, and emotionality as properties of temperament – by the Rusalov tests.
The results of the study and their discussion. The most informative personal characteristics that have significant correlation coefficients (0.5–0.7) with markers of the KRG mathematical model are the indicators of emotionality: personal anxiety (Taylor test), subject and social emotionality (Rusalov test). The least informative personal qualities that affect the characteristics of adaptive processes in this form of goal-oriented activity modeling were indicators of functional lateralization. This is probably due to the fact that the sample only included representatives with varying degrees of right-sided lateralization. There were no representatives of the left-hand side. Other personal characteristics: ergicity, plasticity, pace (Rusalov test), as well as an indicator of the subjects ' focus on performance (Jenkins test) – showed varying degrees of correlation with HRV indicators during exercise, but some General pattern has not yet been identified.

References

1. Patent 2468740 RF, IPC8 A61 B 5/00. Method for determining vegetative activity during load testing / B. A. Sadelnikov-no. 2011110624/14; application 21.03.2011; publ. 10.12.2012, Byul. 34. - 8 p.
2. Lapkin M. M. Comparative characteristics of vegetative control and prevention of heart rhythm disorders in adolescents with physical activity / M. M. Lapkin, A. L. Pokhachevsky / / Preventive medicine. – 2014. – № 3 (17). – Pp. 27-31.
3. Pokhachevsky A. L. Vegetative control of heart rate in the dynamics of load tolerance / A. L. Pokhachevsky // Bulletin of restorative medicine. – 2013. – № 1 (53). – Pp. 38-43.