Physiological Avatar Technology with Optimal Planning of the Training Process in Cyclic Sports


This work is devoted to the theoretical justification of a software and technological product that combines latest achievements in the field of mathematical computer modeling, sports physiology, and medicine. We present a review of theoretical foundations and practical solutions of the latest software and technological developments in the field of control over the training process in cyclic sports. We propose a new integrated approach to the training process planning, which combines known technology of the training impulse and a method for modeling individual physiological properties of the athlete’s body on the basis of the physiological avatar technology.

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  1. 1.

    Fitness Trackers Accurately Measure Heart Rate but not Calories Burned. https://med.stanford. edu/news/all-news/2017/05/fitness-trackers-accurately-measure-heart-rate-but-not-calories-burned.html

  2. 2.

    Vinogradov, M.A., Akimov, E.B., and Timme, E.A., Matematicheskoe modelirovanie dinamiki sportivnogo rezul’tata v vidakh sporta na vynoslivost’ (Mathematical Modeling of Sport Results Dynamics in Stamina Sports), Pushchino: R&C Dynamics, 2015.

    Google Scholar 

  3. 3.

    Solodyannikov, Yu.V., Elementy matematicheskogo modelirovaniya i identifikatsiya sistemy krovoobrashcheniya (Elements of Mathematical Modeling and Identification of the Blood Circulation System), Samara: Samar. Univ., 1994.

    Google Scholar 

  4. 4.

    Proshin, A.P. and Solodyannikov, Yu.V., Mathematical Modeling of Blood Circulation System and Its Practical Application, Autom. Remote Control, 2006, vol. 67, no. 2, pp. 329–341.

    MathSciNet  Article  MATH  Google Scholar 

  5. 5.

    Proshin, A.P. and Solodyannikov, Yu.V., Identification of the Parameters of Blood Circulation System, Autom. Remote Control, 2010, vol. 71, no. 8, pp. 1629–1647.

    MathSciNet  Article  MATH  Google Scholar 

  6. 6.

    Proshin, A.P. and Solodyannikov, Yu.V., Mathematical Modeling of Lactate Metabolism with Applications to Sports, Autom. Remote Control, 2013, vol. 74, no. 6, pp. 1004–1019.

    MathSciNet  Article  MATH  Google Scholar 

  7. 7.

    Ljung, L., System Identification: Theory for the User, Englewood Cliffs: Prentice Hall, 1987. Translated under the title Identifikatsiya sistem. Teoriya dlya pol’zovatelya, Moscow: Nauka, 1991.

    Google Scholar 

  8. 8.

    Janssen, P., Lactate Threshold Training, Champaign: Human Kinetics, 2001.

    Google Scholar 

  9. 9.

    Banister, E.W., Modeling Elite Athletic Performance, in Physiological Testing of Elite Athletes, Macdougall, J.D., Wenger, H.A., Green, H.J., Eds., Champaign: Human Kinetics, 1991.

  10. 10.

    Training Impulse. The Website for All Your Training Load Views, News and Reviews. http://www.

  11. 11.

    Timme, E.A., Applying Imitational Modeling for Planning and Optimization of Training Loads for Sporsmen and People of Dangerous Professions, in Imitational Modeling. Theory and Practice, 7th Russ. Conf., Vassilyev, S.N. and Yusupov, R.M., Eds., Moscow: Inst. Probl. Upravlen., 2015, vol. 2, pp. 361–369.

    Google Scholar 

  12. 12.

    Borresen, J. and Lambert, M., The Quantification of Training Load, the Training Response and the Effect on Performance, Sports Medicine, 2009, vol. 39, no. 9, pp. 779–795.

    Article  Google Scholar 

  13. 13.

    Conconi, F., Ferrari, M., Ziglio, P., Droghetti, P., and Codeca, L., Determination of the Anaerobic Threshold by a Non-invasive Field Test in Runners, J. Appl. Physiol., 1982, vol. 52, no 4, pp. 869–873.

    Article  Google Scholar 

  14. 14.

    Manzi, V., Iellamo, F., Impellizzeri, F., D’Ottavio, S., and Castagna, C., Relation Between Individual Training Impulses and Performance in Dstance Runners, Medicine Sci. Sports Exercise, 2009, vol. 41, no. 11, pp. 2090–2096.

    Article  Google Scholar 

  15. 15.

    Issurin, V.B., Blokovaya periodizatsiya sportivnoi trenirovki (Block Periodization of Sports Training). Moscow: Sovetskii Sport, 2010.

    Google Scholar 

  16. 16.

    Rastrigin, L.A., Adaptatsiya slozhnykh sistem (Adaptation of Complex Systems), Riga: Zinatne, 1981.

    Google Scholar 

  17. 17.

    Coaching Toolkit for Cyclical Sports.

  18. 18.

    Coaching Toolkit for Kayaking and Canoeing.

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Correspondence to A. P. Proshin.

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Original Russian Text © A.P. Proshin, Yu.V. Solodyannikov, 2018, published in Avtomatika i Telemekhanika, 2018, No. 5, pp. 119–136.

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Proshin, A.P., Solodyannikov, Y.V. Physiological Avatar Technology with Optimal Planning of the Training Process in Cyclic Sports. Autom Remote Control 79, 870–883 (2018).

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  • cyclic sport
  • mathematical model
  • training
  • optimal planning