Advertisement

Discrimination Capabilities of Professionals in Manual Skills in a Haptic Task Not Related to Their Expertise

  • Marcos Hilsenrat
  • Miriam Reiner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6192)

Abstract

In this study we present a comparative research between the discrimination capabilities of two populations: Professionals in manual skills and non-professionals, in a task that was not related to their field of expertise. The task was, in a psychophysical test, to discriminate between surfaces of different roughness by indirect touch, using a 3D hapto-visual virtual reality (VR) device. In a texture-difference recognition test subjects glided a pen-like stylus on a virtual surface. The surface was divided into five areas: one central, and four surrounding areas. The roughness of the central area was kept constant throughout the experiment. In each run, three of the four surrounding areas were kept at the same roughness as the central surface, and one, randomly, was different. From run to run, surface roughness was changed following a binary search paradigm. If a subject recognized the portion of the surface with a different roughness, then the roughness was reduced by half; if not, the roughness increased, and so on, until the desired degree of accuracy was achieved. Five professionals from different haptic expertise fields and five non professionals participated in the experiment. The results of the study showed that laymen were significantly more sensitive than experts on roughness discrimination (p < 0.01). These results may suggest that intensive manual activity that demands particular haptic expertise may have a negative impact on manual tasks that are irrelevant to their daily professional activity.

Keywords

experts performance roughness sensitivity virtual reality 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ragert, P., Schmidt, A., Altenmüler, E., Dinse, H.R.: Superior Tactile performance and learning in professional pianists: evidence for meta-plasticity in musicians. Euro Journal of Neuroscience 19(2), 473–478 (2004)CrossRefGoogle Scholar
  2. 2.
    Barret, J., Krueger, H.: Performance effects of reduced proprioceptive feedback on touch typist and casual users in a typing task. Behavior and Information Technology 13(6), 673–681 (1994)Google Scholar
  3. 3.
    Ellis, R., Lederman, S.: The golf-ball illusion: evidence for top-down processing in weight perception. Perception 27, 193–201 (1998)CrossRefGoogle Scholar
  4. 4.
    Lederman, S.J.: Tactile roughness of grooved surfaces: The touching process and effects of macro and microsurface structure. Perception & Psychophysics 16, 385–395 (1974)CrossRefGoogle Scholar
  5. 5.
    Lederman, S.J., Taylor, M.M.: Fingertip force, surface geometry and the perception of roughness by active touch. Perception & Psychophysics 12, 401–408 (1972)CrossRefGoogle Scholar
  6. 6.
    Connor, C.E., Hsiao, S.S., Phillips, J.R., Johnson, K.O.: Tactile roughness: Neural codes that account for psychophysical magnitude estimates. J. Neuroscience 10, 3823–3836 (1990)Google Scholar
  7. 7.
    Klatzky, R.L., Lederman, S.J., Hamilton, C., Grindley, M., Swendsen, R.H.: Feeling textures through a probe: Effects of probe and surface geometry and exploratory factors. Perception & Psychophysics 65(4), 613–631 (2003)CrossRefGoogle Scholar
  8. 8.
    Klatzky, R.L., Lederman, S.J.: Tactile roughness perception with a rigid link interposed between skin and surface. Perception & Psychophysics 61, 591–607 (1999)CrossRefGoogle Scholar
  9. 9.
    Hollins, M., Lorenz, F., Harper, D.: Somatosensory coding of roughness: The effect of texture adaptation in indirect and indirect touch. J. Neuroscience 26(20), 5582–5588 (2006)CrossRefGoogle Scholar
  10. 10.
    Lederman, S.J., Klatzky, R.L., Hamilton, C.L., Ramsay, G.L.: Perceiving roughness via a rigid probe: Psychophysical effects of exploration speed and mode of touch. Elec. J. Haptics Res. 1(1), 1–20 (1999)Google Scholar
  11. 11.
    Gaggioli, A.: Using virtual reality in experimental psychology. In: Riva, G., Galimberti, C. (eds.) Toward Cyber Psychology: Mind, Cognitions and Society in the Internet Age, pp. 157–174. IOS, Amsterdam (2002)Google Scholar
  12. 12.
    Hecht, D., Reiner, M.: Field dependency and the sense of object-presence in haptic virtual environments. Cyberpsychol. Behavior 10(2), 243–251 (2007)CrossRefGoogle Scholar
  13. 13.
    Hilsenrat, M., Reiner, M.: The impact of unaware perception on bodily interaction in virtual reality environments. Presence 18(6), 413–420 (2009)CrossRefGoogle Scholar
  14. 14.
    Reachin API 3.2 Programmers Guide, pp. 10–11 (2003) Google Scholar
  15. 15.
    Hilsenrat, M., Reiner, M.: Hapto-visual virtual reality as a tool in psychophysical research on roughness sensitivity. In: Proceedings of the 3rd International Conference on Advances in Computer-Human Interactions (ACHI 2010), pp. 139–142. IEEE Computer Society Press, Los Alamitos (2010)CrossRefGoogle Scholar
  16. 16.
    Tyrrell, R.A., Owens, D.A.: A rapid technique to assess the resting states of the eyes and other thrshold phenomena: the modified binary search (MOBS). Behavior Research Methods, Instruments, and Computers 20(2), 137–141 (1988)CrossRefGoogle Scholar
  17. 17.
    Faul, F., Erdfelder, E., Lang, A.G., Buchner, A.: G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods 39, 175–191 (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Marcos Hilsenrat
    • 1
  • Miriam Reiner
    • 1
  1. 1.Laboratory of Virtual Reality and Neurocognition, Department of Education in Technology and Science TechnionIsrael Institute of TechnologyHaifaIsrael

Personalised recommendations