Relocating the haptic feedback from the fingertip to the wrist is a trendy topic in haptic-assisted virtual interactions, and finding its best practices still requires a lot of research. In this paper, we investigate the perceptual and performance differences while rendering haptic feedback on the wrist in single-bump, discrete force feedback (through custom voice coil actuation of CoWrHap) or continuous force feedback (through linear DC actuation of LAWrHap). We conducted a user study experiment where participants interacted with identical-looking virtual objects with different stiffness properties and identified the ones with a higher stiffness level based on the haptic feedback they received. Our results indicate that participants performed the tasks (i) with higher sensitivity (higher JND), with more confidence (Number of Taps), and with better user experience using LAWrHap compared to using CoWrHap, and (ii) with no difference in terms of task accuracy (PSE), exploration and interaction time between using LAWrHap and CoWrHap.

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Effects of Rendering Discrete Force Feedback on the Wrist During Virtual Exploration

  • Samet Mert Ercan,
  • Ayoade Adeyemi,
  • Mine Sarac

摘要

Relocating the haptic feedback from the fingertip to the wrist is a trendy topic in haptic-assisted virtual interactions, and finding its best practices still requires a lot of research. In this paper, we investigate the perceptual and performance differences while rendering haptic feedback on the wrist in single-bump, discrete force feedback (through custom voice coil actuation of CoWrHap) or continuous force feedback (through linear DC actuation of LAWrHap). We conducted a user study experiment where participants interacted with identical-looking virtual objects with different stiffness properties and identified the ones with a higher stiffness level based on the haptic feedback they received. Our results indicate that participants performed the tasks (i) with higher sensitivity (higher JND), with more confidence (Number of Taps), and with better user experience using LAWrHap compared to using CoWrHap, and (ii) with no difference in terms of task accuracy (PSE), exploration and interaction time between using LAWrHap and CoWrHap.