Displacements in Virtual Reality for Sports Performance Analysis

Chapter

Abstract

In real situations, analyzing the contribution of different parameters on sports performance is a difficult task. In a duel for example, an athlete needs to anticipate his opponent’s actions to win. To evaluate the relationship between perception and action in such a duel, the parameters used to anticipate the opponent’s action must then be determined. Only a fully standardized and controllable environment such as virtual reality can allow this analysis. Nevertheless, movement is inherent in sports and only a system providing a complete freedom of movements of the immersed subject (including displacements) would allow the study of the link between visual information uptake and action, that is related to performance. Two case studies are described to illustrate such use of virtual reality to better understand sports performance. Finally, we discuss how the introduction of new displacement devices can extend the range of applications in sports.

Keywords

virtual reality sports displacement perception-action coupling locomotion 

References

  1. 1.
    Abernethy B (1985) Cue usage in open motor skills: a review of available procedures. Motor memory and control. Human Performance Associates, OtagoGoogle Scholar
  2. 2.
    Abernethy B (1987) Anticipation in sport: a review. Phys educ rev 10(1):5–16Google Scholar
  3. 3.
    Abernethy B (1988) Dual-task methodology and motor skills research: Some applications and methodological constraints. J Hum Mov Study 14:101–132Google Scholar
  4. 4.
    Abernethy B, Gill D, Parks S, Packer S (2001) Expertise and the perception of kinematic and situational probability information. Perception 30:233–252CrossRefGoogle Scholar
  5. 5.
    Abernethy B, Russell D (1984) Advance cue utilisation by skilled cricket batsmen. Aust J Sci Med Sport 16(2):2–10Google Scholar
  6. 6.
    Abernethy B, Russell D (1987) The relationship between expertise and visual search strategy in a racquet sport. Hum mov sci 3:283–319CrossRefGoogle Scholar
  7. 7.
    Allard F, Starkes J (1980) Perception in sport: volleyball. J Sport Psychol 2:22–33Google Scholar
  8. 8.
    Bard C, Fleury M (1981) Considering eye movement as a predictor of attainment. Vision sport pp 28–41Google Scholar
  9. 9.
    Barfield W, Weghorst S (1993) The sense of presence within virtual environments: A conceptual framework. Proc Fifth Int Conf on Hum-Comput Inter 2:699–704Google Scholar
  10. 10.
    Barfield W, Zeltzer D, Sheridan T, Slater M (1995) Presence and performance within virtual environments. Oxford University Press, Inc, New York, NY, USA, pp 473–513CrossRefGoogle Scholar
  11. 11.
    Bideau B, Kulpa R, Menardais S, Fradet L, Multon F, Delamarche P, Arnaldi B (2003) Presence: Teleoperators & Virtual Environments. Real Handball Goalkeeper vs. Virtual Handball Thrower 12(4):411–421Google Scholar
  12. 12.
    Bideau B, Kulpa R, Vignais N, Brault S, Multon F, Craig C (2010) Using virtual reality to analyze sports performance. IEEE Comput Graphics Appl 30(2):14–21Google Scholar
  13. 13.
    Bideau B, Multon F, Kulpa R, Fradet L, Arnaldi B, Delamarche P (2004) Using virtual reality to analyze links between handball thrower kinematics and goalkeeper’s reactions. Neurosci Lett 372(1–2):119–122CrossRefGoogle Scholar
  14. 14.
    Blair SN (2009) Physical inactivity: the biggest public health problem of the 21st century. Br J Sports Med 43(1):1–2MathSciNetGoogle Scholar
  15. 15.
    Brault S, Bideau B, Kulpa R, Craig C (2012) Detecting deception in movement: The case of the side-step in rugby. PlosOne 7(6):e37494Google Scholar
  16. 16.
    Brault S, Bideau N, Bideau B, Duliscouët L, Marin A, Multon F, Kulpa R Virtual kicker vs. real goalkeeper in soccer: the influence of the wall positioning strategy on the goalkeeper’s performance. J Sports Sci (submitted)Google Scholar
  17. 17.
    Buckolz E, Prapavesis H, Fairs J (1988) Advance cues and their use in predicting tennis passing shots. Canadian journal of sport sciences=. Journal canadien des sciences du sport 13(1):20Google Scholar
  18. 18.
    Cañal-Bruland R, Schmidt M (2009) Response bias in judging deceptive movements. Acta psychol 130(3):235–240CrossRefGoogle Scholar
  19. 19.
    Craig C, Berton E, Rao G, Fernandez L, Bootsma R (2006) Judging where a ball will go: the case of curved free kicks in football. Naturwissenschaften 93(2):97–101CrossRefGoogle Scholar
  20. 20.
    Craig C, Goulon C, Berton E, Rao G, Fernandez L, Bootsma R (2009) Optic variables used to judge future ball arrival position in expert and novice soccer players. Attention, Perception, & Psychophysics 71(3):515–522CrossRefGoogle Scholar
  21. 21.
    Crognier L, Fery Y (2007) 40 years of research on anticipation in tennis: A critical review. Science et Motricit 62:9CrossRefGoogle Scholar
  22. 22.
    Davids K (1984) The role of peripheral vision in ball games: Some theoretical and practical notions. Phys Edu Rev (PER) 7(1):26–40Google Scholar
  23. 23.
    Dessing JC, Craig CM (2010) Bending it like beckham: how to visually fool the goalkeeper. PLoS ONE 5(10), e13,161Google Scholar
  24. 24.
    Farrow D, Abernethy B (2003) Do expertise and the degree of perception: action coupling affect natural anticipatory performance? Perception 32(9):1127–1139CrossRefGoogle Scholar
  25. 25.
    Fery Y, Crognier L (2001) On the tactical significance of game situations in anticipating ball trajectories in tennis. Res Q Exerc sport 72(2):143CrossRefGoogle Scholar
  26. 26.
    Franks I, Harvey I (1997) Cues for goalkeepers-high-tech methods used to measure penalty shot response. Soccer Journal-Binghatmon-National Soccer Coaches Association of. America 42:30–33Google Scholar
  27. 27.
    Gibson J (1979) The Ecological Approach to Perception. Haughton Mifflin, BostonGoogle Scholar
  28. 28.
    Goulet C, Bard C, Fleury M (1989) Expertise differences in preparing to return a tennis serve: A visual information processing approach. J Sport Exerc Psychol 11(4):382–398Google Scholar
  29. 29.
    Helsen W, Pauwels J (1993) The relationship between expertise and visual information processing in sport. Adv psychol 102:109–134CrossRefGoogle Scholar
  30. 30.
    Hendrix C (1994) Exploratory studies on the sense of presence in virtual environments as a function of visual and auditory display parameters. Ph.D. thesis, University of WashingtonGoogle Scholar
  31. 31.
    Hendrix C, Barfield W (1996) Presence within virtual environments as a function of visual display parameters. Presence: Teleoperators and Virtual Environments 5(3), 274–289Google Scholar
  32. 32.
    Hugues C (1999) The F.A. coaching book of soccer tactics and skills. Harpenden: Queen Anne PressGoogle Scholar
  33. 33.
    Jackson R, Warren S, Abernethy B (2006) Anticipation skill and susceptibility to deceptive movement. Acta Psychol 123(3):355–371CrossRefGoogle Scholar
  34. 34.
    Jones C, Miles T (1978) Use of advance cues in predicting the flight of a lawn tennis ball. J hum mov stud 4:231–235Google Scholar
  35. 35.
    Kelly A, Hubbard M (2000) Design and construction of a bobsled driver training simulator. Sports Eng 3(1):13–24CrossRefGoogle Scholar
  36. 36.
    Kulpa R, Multon F, Arnaldi B (2005) Morphology-independent representation of motions for interactive human-like, animation. pp. 343–352Google Scholar
  37. 37.
    Mazyn L, Lenoir M, Montagne G, Savelsbergh G (2004) The contribution of stereo vision to one-handed catching. Exp Brain Res 157(3):383–390CrossRefGoogle Scholar
  38. 38.
    McMorris T, Colenso S (1996) Anticipation of professional soccer goalkeepers when facing right-and left-footed penalty kicks. Percept mot skills 82(3):931–934CrossRefGoogle Scholar
  39. 39.
    McMorris T, Copeman R, Corcoran D, Saunders G, Potter S (1993) Anticipation of soccer goalkeepers facing penalty kicks. Sci footb II:250–253Google Scholar
  40. 40.
    Mori S, Ohtani Y, Imanaka K (2002) Reaction times and anticipatory skills of karate athletes. Hum Mov Sci 21(2):213–230CrossRefGoogle Scholar
  41. 41.
    Multon F, Kulpa R, Bideau B (2008) Mkm: a global framework for animating humans in virtual reality applications. Presence: Teleoper. Virtual Environ. 17(1), 17–28Google Scholar
  42. 42.
    Noser H, Pandzic I, Capin T, Thalmann N, Thalmann D (1997) Playing games through the virtual life network. Artif life five 5:135Google Scholar
  43. 43.
    Ranganathan R, Carlton L (2007) Perception-action coupling and anticipatory performance in baseball batting. J mot behav 39(5):369–380CrossRefGoogle Scholar
  44. 44.
    Ripoll H, Kerlirzin Y, Stein J, Reine B (1995) Analysis of information processing, decision making, and visual strategies in complex problem solving sport situations. Hum Mov Sci 14(3):325–349CrossRefGoogle Scholar
  45. 45.
    Salmela J, Fiorito P (1979) Visual cues in ice hockey goaltending. Can J appl sport sci 4(1):56–59Google Scholar
  46. 46.
    Savelsbergh G, Van der Kamp J, Williams A, Ward P (2005) Anticipation and visual search behaviour in expert soccer goalkeepers. Ergonomics 48(11–14):1686–1697CrossRefGoogle Scholar
  47. 47.
    Savelsbergh G, der Williams A, kamp JV (2002) Visual search, anticipation and expertise in soccer goalkeepers. J Sports Sci 20(3):279–287CrossRefGoogle Scholar
  48. 48.
    Sebanz N, Shiffrar M (2009) Detecting deception in a bluffing body: The role of expertise. Psychon bull rev 16(1):170–175CrossRefGoogle Scholar
  49. 49.
    Shank M, Haywood K (1987) Eye movements while viewing a baseball pitch. Percept Mot Skills 64(3):1191–1197CrossRefGoogle Scholar
  50. 50.
    Singer R, Cauraugh J, Chen D, Steinberg G, Frehlich SG (1996) Visual search, anticipation, and reactive comparisons between highly-skilled and beginning tennis players. J Appl Sport Psychol 8(1):9–26CrossRefGoogle Scholar
  51. 51.
    Slater M (1999) Measuring Presence: A Response to the Witmer and Singer Presence Questionnaire. Presence 8(5):560–565CrossRefGoogle Scholar
  52. 52.
    Slater M, Linakis V, Usoh M, Kooper R (1996) Immersion, presence and performance in virtual environments: an experiment with tri-dimensional chess. ACM Virtual Reality Software and Technology (VRST) pp 163–172Google Scholar
  53. 53.
    Slater M, Usoh M (1993) Presence in immersive virtual environments. In: I. Conference (ed.) Virtual Reality Annual International, Symposium, pp 90–96Google Scholar
  54. 54.
    Tyldesley D, Bootsma R, Bomhoff G (1982) Skill level and eye movement patterns in a sport oriented reaction time task. Motor learning and movement behavior: Contribution to learning in sports pp 290–296Google Scholar
  55. 55.
    Usoh M, Catena E, Arman S, Slater M (2000) Presence questionnaires in reality. Presence: Teleoperators and Virtual Environments 9(5), 497–503Google Scholar
  56. 56.
    Vignais N, Kulpa R, Craig C, Bideau B Virtual thrower versus real goalkeeper: the influence of different visual conditions on performance. Presence: Teleoper. Virtual Environ. 19, 281–290Google Scholar
  57. 57.
    Watson G, Brault S, Kulpa R, Bideau B, Butterfield J, Craig C (2010) Judging the ’passability’ of dynamic gaps in a virtual rugby environment. Hum Mov Sci 30(5):952–956Google Scholar
  58. 58.
    Williams A, Burwitz L (1993) Advance cue utilization in soccer. Science and football II:239–244Google Scholar
  59. 59.
    Williams A, Davids K (1998) Visual search strategy, selective attention, and expertise in soccer. Res Q Exerc Sport 69(2):111–28CrossRefGoogle Scholar
  60. 60.
    Williams A, Davids K, Burwitz L, Williams J (1992) Perception and action in sport. Journal of Human Movement Studies 22:147–204Google Scholar
  61. 61.
    Williams A, Davids K (1999) Williams. Visual perception and action in sportGoogle Scholar
  62. 62.
    Williams A, Elliott D (1999) Anxiety, expertise, and visual search strategy in karate. J Sport Exerc PsycholGoogle Scholar
  63. 63.
    Williams AM, Davids K, Burwitz L, Williams J (1994) Visual search strategies of experienced and inexperienced soccer players. Research Quarterly for Exercise and Sport 65:127–135CrossRefGoogle Scholar
  64. 64.
    Witmer B, Singer M (1998) Measuring Presence in Virtual Environments: A Presence Questionnaire. Presence 7(3):225–240CrossRefGoogle Scholar
  65. 65.
    Zatsiorsky V, Seluyanov V, Chugunova L (1990) Methods of determining mass-inertial characteristics of human body segments. Contemporary Problems of, Biomechanics , pp 272–291Google Scholar
  66. 66.
    von Zitzewitz J, Wolf P, Novakovic V, Wellner M, Rauter G, Brunschweiler A, Riener R (2008) Real-time rowing simulator with multimodal feedback. Sports Technology 1(6):257–266CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Richard Kulpa
    • 1
  • Benoit Bideau
    • 1
  • Sébastien Brault
    • 1
  1. 1.M2S Lab, University of Rennes 2 BruzFrance

Personalised recommendations