ORIGINAL PAPER
Efficiency factors in 110-metre hurdle clearance techniques: kinematics among specialist hurdlers and decathletes
1
ISSEP Ksar-Said, Manouba University, 2010 Manouba, Tunisia
2
Department of Physical Education, College of Education, King Faisal University, Al-Ahsa 31982, Saudi Arabia
Submission date: 2023-10-08
Acceptance date: 2024-01-25
Publication date: 2024-03-22
Hum Mov. 2024;25(1):84-96
KEYWORDS
TOPICS
ABSTRACT
Purpose:
Technical differences may explain why elite hurdles specialists (EHS) and elite decathletes (ED) perform differently in the 110-metre hurdles. This study aims to compare the hurdle-unit kinematic parameters in EHS and ED.
Methods:
A total of 20 male athletes were recruited, including 10 EHS (age: 20.9 ± 2.2 years, body mass: 76.9 ± 7.0 kg, height: 1.85 ± 0.05 m) and 10 ED (age: 20.8 ± 2.27 years, body mass: 87.7 ± 6.9 kg, height: 1.91 ± 0.03 m). Their three-dimensional movement was analysed for hurdling sequences over the whole hurdle-crossing phase and the entire cycle of the first stride after the hurdle, with spatial, temporal, and angular characteristics compared between groups.
Results:
EHS were characterised by faster hurdle crossing (p = 0.002), shorter stride length over the hurdle (p = 0.002), and a shorter support phase in the first stride post-hurdle (p = 0.005). The centre of mass (CM) path of ED was higher than that of EHS (p = 0.003). EHS attack the hurdle with the lead leg’s knee significantly more flexed (p = 0.001) and after crossing the hurdle, regain contact with the ground with the lead leg more flexed at the hip level (p = 0.004), the trunk more inclined forward (p = 0.01), and a relatively smaller positioning angle of the supporting leg (p = 0.021).
Conclusions:
EHS can be identified by their reduced impulse time, abbreviated take-off phase over the hurdle, and accelerated landing. Furthermore, EHS achieved optimum speed between obstacles faster, resulting in less speed loss and enhanced performance.
Technical differences may explain why elite hurdles specialists (EHS) and elite decathletes (ED) perform differently in the 110-metre hurdles. This study aims to compare the hurdle-unit kinematic parameters in EHS and ED.
Methods:
A total of 20 male athletes were recruited, including 10 EHS (age: 20.9 ± 2.2 years, body mass: 76.9 ± 7.0 kg, height: 1.85 ± 0.05 m) and 10 ED (age: 20.8 ± 2.27 years, body mass: 87.7 ± 6.9 kg, height: 1.91 ± 0.03 m). Their three-dimensional movement was analysed for hurdling sequences over the whole hurdle-crossing phase and the entire cycle of the first stride after the hurdle, with spatial, temporal, and angular characteristics compared between groups.
Results:
EHS were characterised by faster hurdle crossing (p = 0.002), shorter stride length over the hurdle (p = 0.002), and a shorter support phase in the first stride post-hurdle (p = 0.005). The centre of mass (CM) path of ED was higher than that of EHS (p = 0.003). EHS attack the hurdle with the lead leg’s knee significantly more flexed (p = 0.001) and after crossing the hurdle, regain contact with the ground with the lead leg more flexed at the hip level (p = 0.004), the trunk more inclined forward (p = 0.01), and a relatively smaller positioning angle of the supporting leg (p = 0.021).
Conclusions:
EHS can be identified by their reduced impulse time, abbreviated take-off phase over the hurdle, and accelerated landing. Furthermore, EHS achieved optimum speed between obstacles faster, resulting in less speed loss and enhanced performance.
REFERENCES (42)
1.
Babić V, Harasin D, Dizdar D. Relations of the variables of power and morphological characteristics to the kinematic indicators of maximal speed running. Kinesiology. 2007;39(1):28–39.
2.
Čoh M, Bončina N, Štuhec S, Mackala K. Comparative biomechanical analysis of the hurdle clearance technique of Colin Jackson and Dayron Robles: key studies. Appl Sci. 2020;10(9):3302; doi: 10.3390/app10093302.
3.
Bedini R. Technical ability in the women’s 100m hurdles. NSA. 2016;31(3/4):117–132.
4.
Tsiokanos A, Tsaopoulos D, Giavroglou A, Tsarouchas E. Race pattern of men’s 110-m hurdles: time analysis of olympic hurdle performance. Biol Exerc. 2018;14(2): 15–36; doi: 10.4127/jbe.2018.0136.
5.
González-Frutos P, Veiga S, Mallo J, Navarro E. Spatiotemporal comparisons between elite and high-level 60 m hurdlers. Front Psychol. 2019;10:2525; doi: 10.3389/fpsyg.2019.02525.
6.
Park YJ, Ryu JK, Ryu JS, Kim TS, Hwang WS, Park SK, et al. Kinematic analysis of hurdle clearance technique for 110-m men’s hurdlers at IAAF world championships, Daegue 2011. KJSB. 2011;21(5):529–540; doi: 10.5103/KJSB.2011.21.5.529.
7.
Amara S, Mkaouer B, Chaabene H, Negra Y, Ben-Salah F. Key kinetic and kinematic factors of 110-m hurdles performance. J Phys Educ Sport. 2019;19(1):658– 668; doi:10.7752/jpes.2019.01095.
8.
Bezodis IN, Brazil A, von Lieres und Wilkau HC, Wood MA, Paradisis GP, Hanley B, et al. World-class male sprinters and high hurdlers have similar start and initial acceleration techniques. Front Sports Act Living. 2019;1:23; doi: 10.3389/fspor.2019.00023.
9.
López del Amo JL, Rodríguez MC, Hill DW, González JE. Analysis of the start to the first hurdle in 110 m hurdles at the IAAF World Athletics Championships Beijing 2015. J Hum Sport Exerc. 2018;13(3):504–517; doi: 10.14198/jhse.2018.133.03.
10.
McDonald C, Dapena J. Linear kinematics of the men’s 110-m and women’s 100-m hurdles races. Med Sci Sports Exerc. 1991;23(12):1382–1391.
11.
Ryu JK, Chang JK. Kinematic analysis of the hurdle clearance technique used by world top class women’s hurdler. KJSB. 2011;21:131–140.
12.
Salo A, Grimshaw PN, Marar L. 3-D biomechanical analysis of sprint hurdles at different competitive levels. Med Sci Sports Exerc. 1997;29(2):231–237; doi: 10.1097/ 00005768-199702000-00011.
13.
Čoh M, Iskra J. Biomechanical studies of 110 m hurdle clearance technique. Sport Sci. 2012; 5(1):10–14.
14.
Hunter I, Bushnell TD. Steeplechase barriers affect women less than men. J Sports Sci Med. 2006;5(2): 318–322.
15.
Howell DC. Statistical Methods for Psychology. 7th ed. Drive Belmont: Cengage Wadsworth, 94002-3098: USA; 2007. Available from: https://labs.la.utexas.edu/gil... files/2016/05/Statistics-Text.pdf.
16.
Bell ML, Kenward MG, Fairclough DL, Horton NJ. Differential dropout and bias in randomized controlled trials: when it matters and when it may not. BMJ. 2013; 346: e8668; doi: 10.1136/bmj.e8668.
17.
World Medical Association, World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310(20): 2191–2194; doi: 10.1001/jama.2013.281053.
18.
Kampmiller T, Slamka M, Vanderka M. Comparative biomechanical analysis of 110 m hurdles of Igor Kova and Peter Nedelicky. Kinesiol Slov. 1999;5(1/2):26–30.
19.
Hanavan EP. A Mathematical Model of The Human Body. AMRL-TR-64-102. AMRL TR. 1964:1–149.
20.
de Leva P. Adjustments to Zatsiorsky-Seluyanov’s segment inertia parameters. J Biomech. 1996;29(9):1223– 1230; doi: 10.1016/0021-9290(95)00178-6.
21.
Tseng YW, Scholz JP, Valere M. Effects of movement frequency and joint kinetics on the joint coordination underlying bimanual circle drawing. J Mot Behav. 2006; 38(5):383–404; doi: 10.3200/JMBR.38.5.383-404.
22.
Winter DA. Biomechanics and Motor Control of Human Movement. 4th ed. Wiley and Sons: Hoboken; 2009.
23.
Hanley B, Walker J, Paradisis GP, Merlino S, Bissas A. Biomechanics of world-class men and women hurdlers. Front Sports Act Living. 2021;3:704308; doi: 10.3389/ fspor.2021.704308.
24.
Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15(2):155–63; doi: 10.1016/j.jcm. 2016.02.012.
25.
Lenhard W, Lenhard A. Computation of effect sizes. Psychometrica. 2022; doi: 10.13140/RG.2.2.17823.92329. Available from: https://www.psychometrica.de/e..._ size.html.
26.
Hopkins WG. A Scale of magnitudes for effect statistics. In: A New View of Statistics. Internet Society of SportScience. 2002. Available from: http://www.sportsci.org/ resource/stats/effectmag.html.
27.
Shrestha N. Detecting Multicollinearity in regression analysis. Am J Appl Math Stat. 2020;8(2):39–42; doi: 10.12691/ajams-8-2-1.
28.
Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale: Lawrence Erlbaum; 1988.
29.
International Olympic Committee (IOC). Athletics– Men’s Decathlon–Results. 2021. Available from: https:// olympics.com/tokyo-2020/olympic-games/resOG2020-/ pdf/OG2020-/ATH/OG2020-_ATH_ C73U_ATHMDECATH.
30.
Graubner R, Nixdorf E. Biomechanical analysis of the sprint and hurdles events at the 2009 IAAF World Championships in athletics. NSA. 2011;26(1+2):19–53.
31.
Bubanj R, Stankovic R, Rakovic A, Bubanj S, Petrovic P, Mladenovic D. Comparative biomechanical analysis of hurdle clearance techniques on 110 m running with hurdles of elite and non-elite athletes. Serb J Sports Sci. 2008;2(1–4):37–44.
32.
Bezodis NE, Walton SP, Nagahara R. Understanding the track and field sprint start through a functional analysis of the external force features which contribute to higher levels of block phase performance. J Sports Sci. 2019;37(5):560–567; doi:10.1080/02640414.201 8.1521713.
33.
Čoh M, Zvan M, Bončina N, Štuhec S. Biomechanical model of hurdle clearance in 100m hurdle races: a case study. J Anthr Sport Phys Educ. 2019;3(4):3–6; doi: 10.26773/jaspe.191001.
34.
Lee JT. Kinematic analysis of hurdling of elite 110m hurdlers. KJSB. 2009;9(4):761–170; doi: 10.5103/KJSB. 2009.19.4.761.
35.
Čoh M, Dolenec A, Tomazin K, Zvan M. Dynamic, and kinematic analysis of the hurdle clearance technique. In: Čoh M (ed.), Biomechanical Diagnostic Methods in Athletic Training. Ljubljana: Faculty of Sports, Institute of Kinesiology; 2008:109–116.
36.
Čoh M, Zvan M. Kinematic and kinetic study of 110 m hurdle clearance technique. Sport Sci. 2018;10(2):13–17.
37.
Hong SH, Ryu JK. Performance analysis of men’s 110-m hurdles using rhythmic units. KJSB. 2018;28(2):79–85; doi: 10.5103/KJSB.2018.28.2.79.
38.
Li J, Fu D. The kinematic analysis on the transition technique between run and hurdle clearance of 110m hurdles. Conference Proceedings Archive. XVIII ISBS: Hong Kong, 2000.
39.
Fernández-Fernández J, Boullosa DA, Sanz-Rivas D, Abreu L, Filaire E, Mendez-Villanueva A. Psychophysiological stress responses during training and competition in young female competitive tennis players. Int J Sports Medi. 2015;36(01):22–8; doi: 10.1055/s-0034- 1384544.
40.
Guebli A, Reguieg M, Belhadj DL, Benelguemar H, Sba B, Nurtekin E. Kinematical variables analysis of discus throw activity in para-athletics (Class F57) and their relationships with digital level achievement. Part I. Spormetre. J Phys Educ Sport Sci. 2021;19(3):60–70; doi: 10.33689/spormetre.854825.
41.
Rowley LJ, Churchill SM, Dunn M, Wheat J. Effect of hurdling step strategy on the kinematics of the hurdle clearance technique. Sports Biomech. 2021:1–15; doi: 10.1080/14763141.2021.1970214.
42.
Kugler F, Janshen L. Body position determines propulsive forces in accelerated running. J Biomech. 2010;43(2): 343–348; doi: 10.1016/j.jbiomech.2009.07.041.
| eISSN: | 1899-1955 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
