Validation of a Virtual Reality Environment to Study Anticipatory Modulation of Digit Forces and Position

  • Matteo Bianchi
  • Giorgio Grioli
  • Enzo Pasquale Scilingo
  • Marco Santello
  • Antonio Bicchi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6192)


The aim of this paper is to validate a virtual reality (VR) environment for the analysis of the sensorimotor processes underlying learning of object grasping and manipulation. This study was inspired by recent grasping studies indicating that subjects learn skilled manipulation by concurrently modulating digit placement and forces as a function of the position of object center of mass (CM) in an anticipatory fashion, i.e. by modulating a compensatory moment before the onset of object manipulation (object lift onset). Data from real and virtual grasping showed a similar learning trend of digit placement and forces, resulting in successful object roll minimization. Therefore, the overall behavioral features associated with learning real object manipulation were successfully replicated by the present VR environment. The validation of our VR experimental approach is an important preliminary step towards studying more complex hand-object interactions.


VR environment object grasping object manipulation anticipatory grasp control 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Johansson, R.S., Flanagan, J.R.: Coding and use of tactile signals from the fingertips in object manipulation tasks. Nat. Rev. Neurosci. 10, 345–359 (2009)CrossRefGoogle Scholar
  2. 2.
    Lukos, J., Ansuini, C., Santello, M.: Choice of contact points during multi-digit grasping. Effect of predictability of center of mass location. Journal of Neuroscience 96, 3894–3903 (2007)CrossRefGoogle Scholar
  3. 3.
    Fu, Q., Zhang, W., Santello, M.: Anticipatory Planning and Control of Grasp Positions and Forces for Dexterous Two-Digit Manipulation. Journal of Neuroscience (accepted pending minor revisions)Google Scholar
  4. 4.
    Zhang, W., Gordon, A.M., Qiushi Fu, Q., Santello, M.: Manipulation after object rotation reveals independent sensorimotor memory representations of digit positions and forces. Journal of Neurophysiology (in Press)Google Scholar
  5. 5.
    Johansson, R.S., Westling, G.: Coordinated isometric muscle commands adequately and erroneously programmed for the weight during lifting task with precision grip. Experimental Brain Research 71, 59–71 (1988)Google Scholar
  6. 6.
    Johansson, R.S., Westling, G.: Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objects. Experimental Brain Research 56, 550–564 (1984)CrossRefGoogle Scholar
  7. 7.
    Johansson, R.S., Westling, G.: Signals in tactile afferents from the fingers eliciting adaptive motor responses during precision grip. Experimental Brain Research 66, 141–154 (1987)CrossRefGoogle Scholar
  8. 8.
    Lukos, J.R., Ansuini, C., Santello, M.: Anticipatory control of grasping: independence of sensorimotor memories for kinematics and kinetics. Journal of Neuroscience 28, 12765–12774 (2008)CrossRefGoogle Scholar
  9. 9.
    Ernst, M.O., Banks, M.S.: Humans integrate visual and haptic information in a statistically optimal fashion. Nature 415, 429–433 (2002)CrossRefGoogle Scholar
  10. 10.
    Kording, K.P., Wolpert, D.M.: Bayesian integration in sensorimotor learning. Nature 427, 244–247 (2004)CrossRefGoogle Scholar
  11. 11.
    Sensable Technologies, Woburn, MA, USA,

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Matteo Bianchi
    • 1
  • Giorgio Grioli
    • 1
  • Enzo Pasquale Scilingo
    • 1
  • Marco Santello
    • 3
  • Antonio Bicchi
    • 1
    • 2
  1. 1.Centro Interdipartimentale di Ricerca “E. Piaggio”, Facoltà di IngegneriaPisaItaly
  2. 2.Istituto Italiano di Tecnologia (IIT)GenovaItaly
  3. 3.Department of Kinesiology, School of Biological and Health Systems EngineeringArizona State UniversityTempeUSA

Personalised recommendations