Position accuracy and fix rate of athletes in location monitoring
Background: The two main factors determining the quality of motion monitoring are the accuracy of determination of position coordinates and the frequency of position logging (fix rate). Material and methods: A comparative analysis of contemporary photogrammetric, remote sensing and satellite methods shows a lack of uniform requirements in this respect with reference to the same sports. Considering the issue on an intuitive basis only, it seems obvious that the accuracy of position in 100-m sprint cannot be measured in metres, and the frequency of positioning should be sub-second. However, the precise values of these variables are not estimated. A mathematical model was created which enabled the determination of minimum requirements concerning athletes’ position accuracy and fix rate, based on statistical data from sports competitions (the results from 4 Olympic Games and 6 World Championships). Results: The key stage for this model is selecting a representative sample of 68% best results (out of a group of results) which is described by time and speed boundary values. Both variables for the selected sport (the 100-m sprint) were calculated: Mmin=0.93 m (minimum position error value) and fmin=10.88 Hz (minimum position fix rate) which enable distinguishing competitors at the finishing line (statistically, position error 5%). Conclusions: (a) The results achieved by sprinters in 100-m run in the world’s best sports events are sufficient to establish requirements regarding the accuracy and the frequency for the determination of athletes’ position in this event. (b) The statistical distribution best fitted to the population of 100-m results is the left-bounded Burr distribution (4P). (c) The method of establishing requirements for the 100-m run should be applied to other track events in order to verify an intuitive perception consisting in the lowering of accuracy and frequency requirements with an increase in an event’s distance.
-  Ohashi J, Togari H, Isokawa M, Suzuki S. Measuring movement speeds and distance covered during soccer match-play. In: Reilly T, Lees A, Davids K, Murphy WJ, editors. Science and Football, London, England; 1988, 434-440.
-  Kuzora P. Computer-aided game evaluation (CAGE). Gdańsk: Kuzora Publishing; 1996.
-  Aschenbrenner P. Analysis of running of giant slalom on the basis of intergate times. In: Erdmann WS, editor. Lokomocja ‘98 [Locomotion ‘98]. Gdansk, Poland; 1998, 45-48.
-  Ferro A, Rivera A, Pagola I, Ferreruela M, Martin A, Rocandio V. A kinematic study of the sprint events at the 1999 World Championships in Athletics in Sevilla. In: Proceedings of XXth International Symposium on Biomechanics in Sports. Caceres, Spain; 2002, 72-75.
-  Zhang BM, Chu DPK. The study of the Optimal Exchange Technique in 4x100m relay. In: Hong Y, Johns DP, editors. Proceedings of XVIII International Symposium on Biomechanics in Sports. Hong Kong, China. 2000, 810-812.
-  Perš J, Bon M, Kovačič S, Šibila M, Dežman B. Observation and analysis of large-scale human motion. Hum Mov Sci. 2002;21;295-311.
-  Barros RML, Misuta MS, Menezes RP. Analysis of the distances covered by first division Brazilian soccer players obtained with an automatic tracking method. J Sports Sci Med. 2007;6;233-242.
-  Mauthner, T., Koch, C., Tilp, M. and Bischof, H. Visual tracking of athletes in beach volleyball using a single camera. Int J Comp Sci Sport. 2007;6(2);21-34.
-  Connaghan D, Hughes S, May G et al. A sensing platform for physiological and contextual feedback to tennis athletes. In: 6th International Workshop on Body Sensor Networks. Berkeley, USA. 2009, 224-229.
-  Hedley M, Mackintosh C, Shuttleworth R, Humphrey D, Sathyan T, Ho P. Wireless tracking system for sports training indoors and outdoors. Procedia Engineering. 2010;2:2999-3004.
-  Fraunhofer Institute for Integrated Circuits. RedFIR Project. [Available at: http://www.iis.fraunhofer.de] [Accessed on April 2015].
-  IAAF World Championships In Athletics 2009. Biomechanics Project – Berlin 2009 – Analysis of Bolt’s 100m: Race distribution: LAVEG measurement curve and average speed. [Available at: http://iaaf.org] [Accessed on January 2015].
-  Larsson P, Burlin L, Jakobsson E, Henriksson-Larsen K. Analysis of performance in orienteering with treadmill tests and physiological field tests using a differential global positioning system. J Sport Sci. 2002;20:529-535.
-  Terrier P, Schutz Y. How useful is satellite positioning system (GPS) to track gait parameters? A review. J Neuroeng Rehabil. 2005.2-28.
-  Terrier P, Turner V, Schutz Y. GPS analysis of human locomotion: further evidence for long-range correlations in stride-to-stride fluctuations of gait parameters. Hum Mov Sci. 2005;4(1):97-115.
-  Supej M. 3D measurements of Alpine skiing with an inertial sensor motion capture suit and GNSS RTK system. J Sport Sci. 2010. 28(7):759-769.
-  Supej M, Bračič M, Čoh M. The use of a high-end global navigation satellite system in a 100 m sprint. Kinesiologia Slovenica. 2010;16(3):14-22.
-  Castellano J, Casamichana D. Heart rate and motion analysis by GPS in beach soccer. J Sports Sci Med. 2010;9:98-103.
-  Mattes K, Schaffert N. New measuring and on water coaching device for rowing. J Hum Sport Exerc. 2010;5(2):226-239.
-  McDonald JB. Some generalized functions for the size distribution of income. Econometrica. 1984;53:647-663.
-  Tadikamalla PR. A look at the Burr and related distributions. International Statistical Review. 1980;48:337-344.
-  GPS SPS PS. Global Positioning System, Standard Positioning Service, Performance Standard, United States of America Department of Defense; 2008.