Full-text resources of PSJD and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


Preferences help
enabled [disable] Abstract
Number of results
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
  • Russian State University of Physical Education, Sport, Youth and Tourism in Moscow Department of Natural Sciences

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
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.