Current judging of race walking in international competitions relies on subjective human observation to detect illegal gait, which naturally has inherent problems. Incorrect judging decisions may devastate an athlete and possibly discredit the international governing body. The aim of this study was to determine whether an inertial sensor could improve accuracy, monitor every step the athlete makes in training and/or competition. Seven nationally competitive race walkers performed a series of legal, illegal and self-selected pace races. During testing, athletes wore a single inertial sensor (100 Hz) placed at S1 of the vertebra and were simultaneously filmed using a high-speed camera (125 Hz). Of the 80 steps analyzed the high-speed camera identified 57 as illegal, the inertial sensor misidentified four of these measures (all four missed illegal steps had 0.008 s of loss of ground contact) which is considerably less than the best possible human observation of 0.06 s. Inertial sensor comparison to the camera found the typical error of estimate was 0.02 s (95% confidence limits 0.01–0.02), with a bias of 0.02 (±0.01). An inertial sensor can thus objectively improve the accuracy in detecting illegal steps (loss of ground contact) and, along with the ability to monitor every step of the athlete, could be a valuable tool to assist judges during race walk events.
References
[1]
Ziv, G.; Rotstein, A. Physiological characteristics of the preferred transition speed in racewalkers. Med. Sci. Sports Exerc. 2009, 41, 797–804.
[2]
International Association of Athletics Federations. IAAF, Competition Rules 2012–2013; Imprimerie Multiprint: Monaco: Principality of Monaco, 2011; pp. 228–236.
[3]
Knicker, A.; Loch, M. Race walking techinque and judging—The final report of the International Athletic Foundation research project. N. Stud. Athl. 1990, 5, 3–25.
[4]
Osterhoudt, R. The Grace and Disgrace of Race Walking. 2000. Available online: http://www.coachr.org/rw2.htm (accessed on 22 July 2013).
[5]
IAAF. Race Walking Challenge. Available online: http://www.iaaf.org/competitions/iaaf-race-walking-challenge/calendar/2013 (accessed on 6 August 2013).
[6]
Winter, D.A. Kinematics. In Biomechanics and Motor Control of Human Movement, 3rd ed. ed.; John Wiley & Sons Inc.: Hoboken, NJ, USA, 2005; pp. 36–40.
[7]
Hollingworth, A. Visual memory for natural scenes: Evidence from change detection and visual research. Vis. Cogn. 2006, 14, 781–807.
[8]
Simons, D.J.; Chabris, C.F.; Schnur, T.; Levin, D.T. Evidence for preserved representations in change blindness. Conscious. Cogn. 2002, 11, 78–97.
[9]
Neville, J.; Wixted, A.; Rowlands, D.; James, D. Accelerometers: An Underutilized Resource in Sports Monitoring. Proceedings of the Sixth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Brisbane, QLD, Australia; 2010; pp. 287–290.
[10]
Henriksen, M.; Lund, H.; Moe-Nilssen, R.; Bliddal, H.; Danneskiod-Sams？e, B. Test-retest reliability of trunk accelerometric gait analysis. Gait Posture 2004, 19, 288–297.
[11]
Lee, J.B.; Mellifont, R.B.; Burkett, B. The use of a single inertial sensor to identify stride, step, and stance durations of running gait. J. Sci. Med. Sport 2010, 13, 270–273.
[12]
Rowlands, A.; Stone, M.; Eston, R. Influence of speed and step frequency during walking and running on motion sensor output. Med. Sci. Sports Exerc. 2007, 39, 716–727.
[13]
Zijlstra, W.; Hof, A.L. Assessment of spatio-temporal gait parameters from trunk accelerations during human walking. Gait Posture 2003, 18, 1–10.
[14]
Little, C.; Lee, J.B.; James, D.A.; Davison, K. An evaluation of inertial sensor technology in the discrimination of human gait. J. Sports Sci. 2013, 31, 1–7.
[15]
Davey, N.; Wixted, A.J.; Ohgi, Y.; James, D.A. A low Cost Self Contained Platform for Human Motion Analysis; Fuss, F.K., Subic, A., Ujihashi, S., Eds.; Taylor and Francis: London, UK, 2008.
[16]
Lai, A.; James, D.A.; Hayes, J.P.; Harvey, E.C. Semi-automatic calibration technique using six inertial frames of reference. Proc. SPIE 2004, 5274, 531–542.
[17]
Wixted, A.J.; Billing, D.C.; James, D.A. Validation of trunk mounted inertial sensors for analysing running biomechanics under field conditions, using synchronously collected foot contact data. Sports Eng. 2010, 12, 207–212.
[18]
Hopkins, W.G. Measures of reliability in sports medicine and science. Sports Med. 2000, 30, 1–15.
[19]
Hopkins, W.G. Reliability from Consecutive Pairs of Trials [Excel spreadsheet]. Available online: http://www.sportsci.org/resource/stats/xrely.xls (accessed on 19 July 2013).
Mathie, M.; Coster, A.; Lovell, N.; Celler, B.; Lord, S.; Tiedemann, A. A pilot study of long-term monitoring of human movements in the home using accelerometry. J. Telemed. Telecare. 2004, 10, 144–151.
[22]
Zheng, H.; Black, N.D.; Harris, N.D. Position-sensing technologies for movement analysis in stroke rehabilitation. Med. Biol. Eng. Comput. 2005, 43, 413–420.
[23]
Kavanagh, J.J.; Menz, H.B. Accelerometry: A technique for quantifying movement patterns during walking. Gait Posture 2008, 28, 1–15.
[24]
Lee, J.B.; Sutter, K.; Askew, C.; Burkett, B. Identifying symmetry in running gait, using a single inertial sensor. J. Sci. Med. Sport 2010, 13, 559–563.
[25]
Arampatzis, A.; Brüggemann, G.P.; Metzler, V. The effect of speed on leg stiffness and joint kinetics in human running. J. Biomech. 1999, 32, 1349–1353.
[26]
Neumann, H.; Krug, J.; Gohlitz, D. Coordinative Threshold in Race Walking. Proceedings of the ISBS Symposium, Salzburg, Austria, 14–18 July 2006.
