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Journals / Istanbul University Journal of Electrical and Electronics Engineering / 2004 / Cilt: 4 - Sayı: 2

Load optimisation on wingate test using artificial neural networks

Yüksel ÖZBAY
Pages
1155–1159
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

By using exercises results unit load optimisation was realized using artificial neural networks.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In supplying the power loss for a period of time that came out during the physical activities, available energy metabolism on leg muscles plays a very important role.
📊
Key Findings & Data:In Wingate Test (WT) that's developed for the anaerobic power measurement on leg muscles, a person is demanded to pedal a special bicycle for 30 seconds under a determined load.
💡
Conclusion & Impact:By using exercises results unit load optimisation was realized using artificial neural networks.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In supplying the power loss for a period of time that came out during the physical activities, available energy metabolism on leg muscles plays a very important role. In Wingate Test (WT) that's developed for the anaerobic power measurement on leg muscles, a person is demanded to pedal a special bicycle for 30 seconds under a determined load. At first, a unit load (gr/kg) is determined and a friction force, which is proportional to the person's weight, is applied to the pedal-strap. The friction force that'll be applied to bicycle's pedal-strap must be determined. The determination of the unit load values depends on persons' age, weight, sex, and condition of fitness. Wingate anaerobic test was performed on 35 volunteered and untrained male medical students (mean age 21.3 ± 2.1, mean length 172.1 ± 6.3 cm, mean weight 73.5 ± 8.4 kg) at Physiology Department of Medicine Faculty of Selçuk University. By using exercises results unit load optimisation was realized using artificial neural networks.

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Cite This Article

ÖZBAY, Y. (2022). Load optimisation on wingate test using artificial neural networks. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 4 - Sayı: 2, 1155–1159. https://ajindex.com/articles/543883

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References (15)

  1. Margaria R., Aghemo P., Rovellie E., "Measurement of muscle power anaerobic in man", J.Appl. Physiol., 21, 1662-4, 1966
  2. Dotan R., Bar-Or O, "Load of optimization for the Wingate anaerobic test", Eur.J.Appl.Physiol., 51,409-17, Israel, 1983 [3] Katz A., Sahlin K., Henriksson J., "Muscle ATP turn over rate during isometric contraction in humans", J.Apple.Physiol.,60, 1839-42,1986
  3. Patton J.F, Murphy M.M, Frederick F.A, "Maximal power outputs during the wingate anaerobic test", Int.J.Sports Med., 6, 82-85, New York, 1985
  4. Hawleyy J.A, Williams M.M, Hamling G.C, Walsch R.M, "Effects of atask a specific warmup on anaerobic power", Br. J.Sp.Med.Vol.23, No.4, 233-6. New Zealand. 1989
  5. Tharp G.D, Newhouse R.K, Uffelman L., "Thorland W.G, Johnson G.O, Comparison of sprint and run times with performance on the Wingate anaerobik test", Res Q., 56: 73-6, 1985
  6. Patton J.F., Duggan A., "An evaluation of tests of anaerobic power. Aviat Space Environ Med.", 58:237-42, 1987 [8] Maud P. J, Shultz B. B, "Norms for the Wingate anaerobic test with comparison to another similar tests", Research Quarterly for Exersise and Sport, Vol.60, No.2,144-51. Eastern Washington Üniversity. 1989
  7. Nebelsick-Gullet L.J., Housh T.J., Johnson G.O., "Bauge S.M., A comparison between methods of measuring anaerobic work capacity", Ergonomics, 31:1413-9,1988
  8. Manning J.M., Dooly-Manning C., Perrin D.H., "Factor analysis of various anaerobic power tests", J. Sports Med., 28:138-44, 1988
  9. Astrand P.O., Rodahl K., "Textbook of Work Physiology. 3rd ed." McGraw Hill, 384, Singapore, 1986
  10. Inbar O, Ayalon A, Bar-Or O, "Relationship between tests of anaerobic capacity and power", Israel J. Med. Sci., 10, 290-1, 1974
  11. Bar-Or O., Dotan R., Inbar O., "A 30-sec. all-out ergometric test: its reliability and validity for anaerobic capacity", Israel J. Med. Sci., 13:326-7, 1977
  12. Francis K., "Methods of anaerobic power assestment (A statistical program for the IBM PC)", Physical Ther., 67, 270-5,1987
  13. Gökbel H, Dölek Ç, Bediz C.Ş, Kara M, Vural H., "The relationship of lactic acid and total testosterone levels after the Wingate test", Türk J. Med. Sci., 26, 1996
  14. Gökbel H, Çalişkan S, Özbay Y, Bediz C.Ş, "The Anaerobic Power values in Wingate Tests with two different loads", Journal of Sports Science, 4,10-16, 1993
  15. Froese E.A., Houston M.E., "Performance during the Wingate test and muscle morphology in males and females", Int. J. Sports M