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2012 | 19 | 4 | 253-255
Article title

Innovative Modeling Method in Technical Training of High Jumpers

Content
Title variants
Languages of publication
EN
Abstracts
EN
Introduction. This essay introduces an innovative high jump technique modeling method that uses a cascaded fuzzy neural network. An interactive system for the prediction of the success of a high jump has been designed based on this method and it allows the creation of an individual model for highly skilled athletes to control the jumper's technical training. Material and methods. The research material included a video recording of 92 high jumps and analysis by 48 kinematic characteristics. The result allowed the fine tuning of the cascaded fuzzy neural network model in order to analyse successful and failed jumps. Results and conclusions. We have developed the interactive system based on the analysis of kinematic characteristics of the high jump and this allows individual performance models to be tailored for elite athletes. With the help of this instrument, which takes into account the individual biomechanical features of an athlete's jumping style, we can analyze all stages of a jump in detail, improve the technique through the targeted correction of specific motions and achieve the optimal combination of kinematic values for the best possible result.
Publisher

Year
Volume
19
Issue
4
Pages
253-255
Physical description
Dates
published
1 - 12 - 2012
online
20 - 04 - 2013
Contributors
  • Russian State University of Physical Education, Sport, Youth and Tourism, Department of Natural Sciences, Sirenevyi Boulevard 4, Moscow, Russia, tel.: +7 9265824748, fax +7 4991665471, hijumper@mail.ru
  • Russian State University of Physical Education, Sport, Youth and Tourism in Moscow Department of Natural Sciences, hijumper@mail.ru
References
  • 1. Lysenko, V.V. & Romanov D.A. (2004). Managing the technical preparation of high-skill athletes based on computer video analysis of movements.Teorija i Praktika Fizicheskoj Kuľtury: Trener (an insert) 8, 30-31. [in Russian]
  • 2. Krivetskiy, I.Y., Popov G.I. & Bezrukov N.S. (2011). Model- ling the success of motions in high jumps. Informatika i Sistemy Upravlenija 2,126-132. [inRussian]
  • 3. Krivetskiy, I.Y., Popov G.I. & Bezrukov N.S. (2011). Optimization the training process of high jumpers with using the individual model of technique of jump based on a cascaded fuzzy neural network. Scientific Report Series Physical Education and Sport 15, 31-35.
  • 4. Bezrukov, N.S., Eremin E.L., Ermakova E.V., Kolosov V.P. & Perelman J.M. (2006). Automated system “Medical Toolbox” for diagnosing bronchial asthma using rheoencephalography results. Informatika i Sistemy Upravlenija 1, 73-80. [in Russian]
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.-psjd-doi-10_2478_v10197-012-0024-z
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