Heart rate variation profiling by stress tests in precompetitive, competitive and rehabilitation periods

Teoriya i praktika fizicheskoy kultury №7 2019

Dr.Med., Professor A.L. Pokhachevsky1
K.G.K. Abdullayeva1
PhD M.V. Akulina2
PhD, Associate Professor Yu.M. Reksha3
F.R. Gadzhimuradov4
1I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), Moscow
2Ryazan State Medical University named after academician I.P. Pavlov, Ryazan
3The Academy of Law and Management of the Federal Penal Service of Russia, Ryazan
4Ryazan Branch of the Kikot Moscow University of the Ministry of Internal Affairs of Russia, Ryazan

Early heart rate (HR) variations in the precompetitive (PC), competitive (CP) and training (TR) periods are rather critical for the forecasts of the athletes’ physical work capacity and rehabilitation resource. Spearman correlation analysis and practical mathematical modeling (MM) of the PC, CP and TR supported by cardiac rhythmograms (CRG) made it possible to find efficient MM markers for every period versus the rehabilitation (RB) period and find meaningful correlations of the CRG MM for PC and CP versus the TR ones. Fatigue tolerance under workloads may also be rated by the first-minutes CRG and by the precompetitive and competitive chronotropic mobilization rates. Whilst the precompetitive CRG variations precede the physical workload (PW) and the competitive CRG varies with the minimal PW versus the training CRG dependant on the sub-maximal PW, each of the test options may be applied for the customizable PW forecast tests in the cardiologic, rehabilitation and training practices. The HR variability forecasts after the sub-maximal PW may be made based not only on the first-minutes CRG but also on the precompetitive and competitive chronotropic mobilization rates. We found most beneficial for the forecasts the precompetitive, competitive and training mathematical models of the first- and third-minute CRG.

Keywords: cardiac rhythmogram, mathematical model, physical workload tolerance forecast, physical work capacity.

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