The wearable devices application for evaluation of 110 meter high hurdle race

Chin-Shan Ho, Chi-Yao Chang, Kuo-Chuan Lin

Abstract

Purpose: This study was intended to explore the continuous changes in the kinematic parameters of hurdlers in a 110 meter (110m) high hurdle race from hurdles 1 through 10. Method: Ten excellent college athletes who specialized in the 110m high hurdle race volunteered for this study. Inertial measurement units (IMUs) strapped to the back of the athlete’s feet and 10 high-speed cameras were used to document the movements of the hurdlers as they were hurdling along the entire track. Kwon3D and MATLAB computer programs were employed for the analysis of kinematic parameters (take-off distance, landing distance, take-off distance percentage, landing distance percentage, flight time, time between hurdles, hurdle cycle time, hurdle cycle velocity, height of centre gravity above the hurdle and take-off angles). The trend analysis was introduced to test the changes of the parameters between hurdles. The level of significance was set to α =.05. Results: The results showed that the subjects averaged 14.31±0.29 seconds in their 110m high hurdle tests. Regarding the trend analysis, all kinematic parameters except landing distance displayed quadratic linear patterns along the 110m race. Conclusion: The athletes rapidly gained speed as they sprinted from the starting line and reached their maximum speeds between hurdles 5 and 6, after which their speed declined. In addition, the kinematic parameters changed as the running velocity varied.


Keywords

Inertial measurement unit; Flight time; Time between hurdles; Take-off angles

References

Čoh, M., & Iskra, J. (2012). Biomechanical studies of 110 m hurdle clearance technique. Sport Science, 5(1), 10-14.

Coh, M., Jost, B., & Skof, B. (2000). Kinematic and dynamic analysis of hurdle clearance technique. In ISBS-Conference Proceedings Archive (Vol. 1, No. 1).

Dapena, J. (1991). Hurdle clearance technique. Track and Field. Quart. Rev.116 (3), 710- 712.

Dempster, W. T. (1955). Space requirements of the seated operator, geometrical, kinematic, and mechanical aspects of the body with special reference to the limbs. Michigan State Univ East Lansing. https://doi.org/10.21236/AD0087892

El-Hamid, M. G. (2012). Effect of Training by Using the Change in the Official Measurements on Some Special Variables and Record Level of 110m Hurdles Competitors. World Journal of Sport Sciences, 6(2), 152-156.

Favre, J., Aissaoui, R., Jolles, B. M., de Guise, J. A., & Aminian, K. (2009). Functional calibration procedure for 3D knee joint angle description using inertial sensors. Journal of biomechanics, 42(14), 2330-2335. https://doi.org/10.1016/j.jbiomech.2009.06.025

Göpfert, C., Pohjola, M. V., Linnamo, V., Ohtonen, O., Rapp, W., & Lindinger, S. J. (2017). Forward acceleration of the centre of mass during ski skating calculated from force and motion capture data. Sports Engineering, 20(2), 141-153. https://doi.org/10.1007/s12283-016-0223-9

Iskra, J., & Coh, M. (2011). Biomechanical studies on running the 400 m hurdles. Human Movement, 12(4), 315-323. https://doi.org/10.2478/v10038-011-0035-5

Iskra, J., & Wlaszczyk, A. (2007). Types of strides pattern and time distribution in elite 400-m-hurdlers.

Jensen, U., Schmidt, M., Hennig, M., Dassler, F. A., Jaitner, T., & Eskofier, B. M. (2015). An IMU-based mobile system for golf putt analysis. Sports Engineering, 18(2), 123-133. https://doi.org/10.1007/s12283-015-0171-9

Kampmiller, T., Slamka, M., & Vanderka, M. (1999). Comparative biomechanical analysis of 110 m hurdles of Igor Kovač and Peter Nedelicky. Kinesiologia Slovenica, 5(1-2), 26-30.

Kavanagh, J. J., Morrison, S., James, D. A., & Barrett, R. (2006). Reliability of segmental accelerations measured using a new wireless gait analysis system. Journal of biomechanics, 39(15), 2863-2872. https://doi.org/10.1016/j.jbiomech.2005.09.012

Kuznietsov, A., & Neubauer, D. (2012, March). A wireless framework for movement activity monitoring of sprinters. In Proceedings of the 9th International Multi-Conference on Systems, Signals and Devices, Chemnitz, Germany (pp. 20-23). https://doi.org/10.1109/SSD.2012.6198028

López del Amo, J. L., Rodríguez, M. C., Hill, D. W., & González, J. E. (2018). Analysis of the start to the first hurdle in 110 m hurdles at the IAAF World Athletics Championships Beijing 2015.

McGrath, D., Greene, B. R., O'Donovan, K. J., & Caulfield, B. (2012). Gyroscope-based assessment of temporal gait parameters during treadmill walking and running. Sports Engineering, 15(4), 207-213. https://doi.org/10.1007/s12283-012-0093-8

Mayagoitia, R. E., Nene, A. V., & Veltink, P. H. (2002). Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems. Journal of biomechanics, 35(4), 537-542. https://doi.org/10.1016/S0021-9290(01)00231-7

Picerno, P., Camomilla, V., & Capranica, L. (2011). Countermovement jump performance assessment using a wearable 3D inertial measurement unit. Journal of sports sciences, 29(2), 139-146. https://doi.org/10.1080/02640414.2010.523089

Radoslav, B., Saša, B., Darko, M., Vladan, P., Aleksandar, R., & Ratko, S. (2008). Comparative biomechanical analysis of hurdle clearance techniques on 110 m running with hurdles of elite and non-elite athletes. Serbian Journal of Sports Sciences, 2, 37-44.

Sato, K., Sands, W. A., & Stone, M. H. (2012). The reliability of accelerometry to measure weightlifting performance. Sports Biomechanics, 11(4), 524-531. https://doi.org/10.1080/14763141.2012.724703

Saber-Sheikh, K., Bryant, E. C., Glazzard, C., Hamel, A., & Lee, R. Y. (2010). Feasibility of using inertial sensors to assess human movement. Manual Therapy, 15(1), 122-125. https://doi.org/10.1016/j.math.2009.05.009

Schluter, W. (1981). Kinematische Merkmale der 110-m Hurdentechnik. Leistungssport, 2, 118-127.

Sidhu, A. S. & Singh, M. (2015). Kinematical analysis of hurdle clearance technique in 110m hurdle race. International Journal of Behavioural Social and Movement Science, 4(2), 28-35.

Stančin, S., & Tomažič, S. (2013). Early improper motion detection in golf swings using wearable motion sensors: The first approach. Sensors, 13(6), 7505-7521. https://doi.org/10.3390/s130607505

Tien, I., Glaser, S. D., Bajcsy, R., Goodin, D. S., & Aminoff, M. J. (2010). Results of using a wireless inertial measuring system to quantify gait motions in control subjects. IEEE Transactions on Information Technology in Biomedicine, 14(4), 904-915. https://doi.org/10.1109/TITB.2009.2021650

Zhao, Y., Gerhard, D., & Barden, J. (2015). Periodicity-based swimming performance feature extraction and parameter estimation. Sports Engineering, 18(3), 177-189. https://doi.org/10.1007/s12283-015-0178-2




DOI: https://doi.org/10.14198/jhse.2020.151.04





License URL: https://creativecommons.org/licenses/by-nc-nd/4.0/