Advertisement

Automation and Remote Control

, Volume 79, Issue 5, pp 870–883 | Cite as

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

  • A. P. Proshin
  • Yu. V. Solodyannikov
Control in Social Economic Systems
  • 29 Downloads

Abstract

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.

Keywords

cyclic sport mathematical model training optimal planning 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  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.htmlGoogle Scholar
  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.MathSciNetCrossRefzbMATHGoogle 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.MathSciNetCrossRefzbMATHGoogle 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.MathSciNetCrossRefzbMATHGoogle 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.zbMATHGoogle 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.Google Scholar
  10. 10.
    Training Impulse. The Website for All Your Training Load Views, News and Reviews. http://www. trainingimpulse.com/Google Scholar
  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.CrossRefGoogle 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.CrossRefGoogle 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.CrossRefGoogle 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.zbMATHGoogle Scholar
  17. 17.
    Coaching Toolkit for Cyclical Sports. https://www.microsoft.com/store/apps/9nzs4c1hcm1dGoogle Scholar
  18. 18.
    Coaching Toolkit for Kayaking and Canoeing. https://www.microsoft.com/store/apps/9nblggh51knqGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2018

Authors and Affiliations

  1. 1.JSC “Samara-Dialog,”SamaraRussia

Personalised recommendations