Article
The purpose of the research is to identify the features of different approaches of environment influence on motor actions.
Research methods. To determine the advantages, disadvantages and limitations of different approaches we analyzed the scientific literature. At the same time, for a deeper understanding of the functionality of various methods, they were directly tested on specific examples (in silico). The main method was computer modeling, including: 3D human body modeling, hydrodynamic forces modeling, modeling of motion kinematics in the environment.
Research results. The article presents four approaches for assessing the environment influence on motor actions: 1) a qualitative analytical approach; 2) an approach based on the summation of forces in the system of levers of the human motor apparatus; 3) an approach based on computational fluid dynamics (CFD); 4) an approach based on recurrent physical and mathematical modeling.
The most efficient is a qualitative analytical approach based on a comparison of the movement directions and forces action vectors. This approach allows getting a fundamental answer whether hydrodynamic forces contribute or hinder motor action without precise quantitative values.The approach based on the summation of forces allows determining the load on compression and twisting in specific joints. However it is applicable only for static or slow movements. Computational fluid dynamics (CFD) approach allows directly watching the flowing process and accurately calculating the nhydrodynamic forces. However, the approach does not take into account the influence of forces themselves on the propulsion and does not allow modeling complex trajectories of movement.
The approach based on recurrent physical and mathematical modeling is the most universal because it let to calculate the motion kinematics. The approach has great prospects due to the possibility of configuring the algorithm and supplementing it with the necessary variables and coefficients.
Conclusion. It is obvious that a complete analysis of the environment influence on the motor actions requires the use of all four presented approaches.
- Adashevskij, V.M, Borodavchenko D.A.. [Physical and mathematical modeling for determining the main biomechanical characteristics in swimming]. Pedagogy, psychology and biomedical problems of physical education and sports, 2007, № 8, pp. 3-5 (In Russ.).
- Pomerantsev, A.A. Issledovaniya po sportivnoj biomekhanike s primeneniem optiko-elektronnyh metodov registracii parametrov dvizheniya [Research on sports biomechanics using optoelectronic methods for recording motion parameters]. Lipetsk, LGPU, 2018. – 233 p. (In Russ.).
- Pomerantsev, A.A. Komp'yuternoe modelirovanie vzaimodejstviya biomekhanicheskoj grebnoj sistemy (BGS) so sredoj [Computer simulation of the interaction of a biomechanical kayaking system (BKS) with the environment]. At the turn of the XXI century. Year 2004: Scientific Almanac of MSAPC / Moscow State Academy of Physical Culture. - Malakhovka: Moscow State Academy of Physical Culture, 2004. – pp. 360-367. (In Russ.).
- Pomerantsev, A.A. Metodika prostranstvennoj rekonstrukcii podvodnoj traektorii dvizheniya vesla kak osnova teoreticheskih i prikladnyh issledovanij v grebnom sporte [The methodology of spatial reconstruction of the underwater trajectory of the paddle movement as the basis of theoretical and applied research in rowing]. Lipetsk, LGPU, 2012. – 184 p.
- Let A.M., Filip V., Let D., Mihai S. A Review in Biomechanics Modeling. Proceedings of the International Conference of Mechatronics and Cyber- MixMechatronics, 2020. DOI:10.1007/978-3-030-53973-3_17
- Forte P., Marinho D.A., Barbosa T.M., Morais J.E. Analysis of a normal and aero helmet on an elite cyclist in the dropped position AIMS Biophysics, March 2020. 7(1), pp. 54-64. DOI: 10.3934/biophy.2020005
- Forte P., Marinho D.A., Nikolaidis P.T., Knechtle B., Barbosa T.M., Morais J.E. Analysis of cyclist’s drag on the aero position using numerical simulations and analytical procedures: a case study. International Journal of Environmental Research and Public Health, May 2020. 17(10), 3430. DOI: 10.3390/ijerph17103430
- Harrison S.M., Cleary P.W., Cohen R.C.Z. Dynamic simulation of flat water kayaking using a coupled biomechanical-smoothed particle hydrodynamics model. Human Movement Science, 2019, Vol. 64, pp. 252-273. DOI:10.1016/j.humov.2019.02.003
- Jiang, L., Research on 3D simulation of swimming technique training based on FPGA and virtual reality technology. Microprocessors and Microsystems, 2021, Vol. 81, 103657 DOI: 10.1016/j.micpro.2020.103657
- Karmanov S. P., Chernous'ko F. L. Modeling of breaststroke swimming. Doklady Physics, 2014, Vol. 59(2), pp. 103-106. DOI: 10.1134/S1028335814020104
- Lighthill, J. Mathematical Biofluiddynamics. Philadelphia, SIAM, – 1975. – 281 p.
- Linthorne, N.P. The effect of wind on 100 m sprint times. Journal of Applied Biomechanics, 1993, 10 (2), pp. 110-131. DOI: 10.1123/jab.10.2.110
- Mureika, J.R. A realistic quasi-physical model of the 100 m dash. Canadian Journal of Physics, 2001, 79(4), pp. 697-713. DOI: 10.1139/p01-031
- Polidori G., Legrand F., Bogard F., Madaci F. Beaumont Numerical investigation of the impact of Kenenisa Bekele’s cooperative drafting strategy on its running power during the 2019 Berlin marathon. Journal of Biomechanics, 2020, Vol. 107, 109854. DOI: 10.1016/j.jbiomech.2020.109854
- Marinho D.A., Willemsen D., Barbosa T.M., Silva A.J., Vilas-Boas J.P., Neiva H.P., Forte P. Numerical simulations of a swimmer’s head and cap wearing different types of goggles. Sports Biomechanics, 2021. DOI: 10.1080/14763141.2021.1923793
- Quinn, M. The effects of wind and altitude in the 400-m sprint. Journal of Sports Sciences, 2004, 22:11-12, pp. 1073-1081. DOI:10.1080/02640410410001730016
