We study the variations in two dimensional (2D) pointing tasks on a traditional white board of a group of subjects by means of capturing their movement traces in an automatic way with the Mimio device. Such traces provide detailed insight in the variability of 2D pointing relevant for example for the design of computer vision based gestural interaction. This study provides experimental evidence that for medium large distances Fitts’ model, and Welfords and Shannons variants, continue to show a linear relationship between movement time (MT) and the index of difficulty (ID) with a high correlation for the ranges considered. The expected increased sensitivity to changes in ID for these larger distances are confirmed. Nearly all movements show three phases: a planning phase, a ballistic phase and an adjustment phase. Finally, we show that the arrival time at the target resembles a log-normal distribution.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Accot, J., Zhai, S.: Beyond Fitts’ law: models for trajectory-based HCI tasks. In: Pemberton, S. (ed.) CHI-Conference on Human Factors in Computing Systems, ACM Press, New York (1997)Google Scholar
  2. 2.
    Barnard, P., May, J.: Representing cognitive activity in complex tasks. International Journal on Human-Computer Interaction 14, 92–158 (1999)Google Scholar
  3. 3.
    Bérard, F.: Vision par ordinateur pour l’interaction homme-macine fortement couplée, Ph.D. thesis (1999)Google Scholar
  4. 4.
    Cipolla, R., Pentland, A.E.: Computer Vision for Human-Machine Interaction. Cambridge University Press, Cambridge (1998)Google Scholar
  5. 5.
    Doherty, G., Massink, M., Faconti, G.: Reasoning about interactive systems with stochastic models. In: Johnson, C. (ed.) DSV-IS 2001. LNCS, vol. 2220, Springer, Heidelberg (2001)CrossRefGoogle Scholar
  6. 6.
    Faconti, G., Massink, M.: Analysis of pointing tasks on a white board - Extended version. CNR-ISTI Technical report 2006-TR-24, CNR (2006)Google Scholar
  7. 7.
    Fitts, P.M.: The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology 47, 381–391 (1954)CrossRefGoogle Scholar
  8. 8.
    Mimio interactive whiteboard (2005),
  9. 9.
    Jagacinski, R.J., et al.: Fitts’ law and the microstructure of rapid discrete movements. Journal of Experimental Psychology: Human Perception and Performance 6(2), 309–320 (1980)CrossRefGoogle Scholar
  10. 10.
    Langolf, G.D., Chaffin, D.B., Foulke, J.A.: An investigation of Fitts’ law using a wide range of movement amplitudes. Journal of Motor Behaviour 8, 113–128 (1976)Google Scholar
  11. 11.
    Letessier, F., Bérard, J.: Visual tracking of bare fingers for interactive surfaces. In: ACM Symposium on User Interface Software and Technology (UIST), Santa Fe, New, Mexico, USA, ACM Press, New York (2004)Google Scholar
  12. 12.
    MacKenzie, I.S.: Fitt’s law as a research and design tool in human-computer interaction. International Journal of Human-Computer Interaction 7, 91–139 (1992)Google Scholar
  13. 13.
    MacKenzie, I.S., Balakrishnan, R.: Performance differences in the fingers, wrist, and forearm in computer input control. In: Pemberton, S. (ed.) CHI-Conference on Human Factors in Computing Systems, ACM Press, New York (1997)Google Scholar
  14. 14.
    MacKenzie, I.S., Soukoreff, W.: Card, english, and burr (1978) – 25 years later. In: Extended Abstracts of the ACM Conference on Human Factors in Computing Systems–CHI, pp. 760–761. ACM Press, New York (2003)Google Scholar
  15. 15.
    Murata, A.: Extending effective target width in Fitts’ law to a two-dimensional pointing task. International Journal of Human-Computer Interaction 11(2), 137–152 (1999)CrossRefGoogle Scholar
  16. 16.
    Shannon, C.E., Weaver, W.: The mathematical theory of communication (1949)Google Scholar
  17. 17.
    Swain, A.D., Guttmann, H.E.: Handbook of human reliability analysis with emphasis on nuclear power plant applications - final report, 1983. Technical Report NRC FIN A 1188 NUREG/CR-1278 SAND80-0200. Prepared for Division of Facility Operations; Office of Nuclear Regulatory Research; Nuclear Regulatory Commission; Washington D.C. 20555Google Scholar
  18. 18.
    Welford, A.T.: The measurement of sensory-motor performance: survery and reappriasal of twelve years’ progress. Ergonomics 3, 189–230 (1960)CrossRefGoogle Scholar
  19. 19.
    Welford, A.T.: Fundamentals of skill (1968)Google Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • G. Faconti
    • 1
  • Mieke Massink
    • 1
  1. 1.Consiglio Nazionale delle Ricerche, Istituto ISTI, PisaItaly

Personalised recommendations