Assessing the Impact of Automatic vs. Controlled Rotations on Spatial Transfer with a Joystick and a Walking Interface in VR

  • Florian Larrue
  • Hélène Sauzéon
  • Déborah Foloppe
  • Grégory Wallet
  • Jean-René Cazalets
  • Christian Gross
  • Martin Hachet
  • Bernard N’Kaoua
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8117)

Abstract

We present a user study assessing spatial transfer in a 3D navigation task, with two different motor activities: a minimal (joystick) and an extensive motor activity (walking Interface), with rotations of the viewpoint either controlled by the user, or automatically managed by the system. The task consisted in learning a virtual path of a 3D model of a real city, with either one of these four conditions: Joystick / Treadmill Vs Manual Rotation / Automatic Rotation. We assessed spatial knowledge with six spatial restitution tasks. To assess the interfaces used, we analyzed also the interaction data acquired during the learning path. Our results show that the direct control of rotations has different effects, depending on the motor activity required by the input modality. The quality of spatial representation increases with the Treadmill when rotations are enabled. With the Joystick, controlling the rotations affect spatial representations. We discuss our findings in terms of cognitive, sensorimotor processes and human computer interaction issues.

Keywords

Interfaces Navigation Virtual Reality Spatial Cognition Joystick Treadmill Rotation Body-based Information Vestibular Information Human Machine Interaction Human Factors User Study Motor Activity 

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Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  • Florian Larrue
    • 1
    • 2
  • Hélène Sauzéon
    • 2
    • 1
  • Déborah Foloppe
    • 3
  • Grégory Wallet
    • 4
  • Jean-René Cazalets
    • 5
  • Christian Gross
    • 6
  • Martin Hachet
    • 1
  • Bernard N’Kaoua
    • 1
    • 2
  1. 1.INRIATalenceFrance
  2. 2.EA 4136, Handicap & Système NerveuxUniversity of Bordeaux Victor SegalenBordeaux CedexFrance
  3. 3.LPPL - (UPRES EA 4638)LUNAM Université - Université d’AngersFrance
  4. 4.CNRS, ISM UMR 7287Aix-Marseille UniversitéMarseille Cedex 09France
  5. 5.CNRS UMR 5287INCIA - Institut de Neurosciences Cognitives et Intégratives d’AquitaineBordeaux CedexFrance
  6. 6.Institut des Maladies Neurodégénératives, CNRS UMR 5293University of Bordeaux Victor SegalenBordeaux CedexFrance

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