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ShareYourReality: Investigating Haptic Feedback and Agency in Virtual Avatar Co-embodiment

Karthikeya Puttur Venkatraj, Wo Meijer, Monica Perusquía-Hernández, Gijs Huisman, Abdallah El Ali

TL;DR

Drawing on the perceptual crossing paradigm, how haptics can enable non-verbal coordination between co-embodied participants is explored and cautionary considerations when including haptic feedback mechanisms for avatar co-embodiment experiences are provided.

Abstract

Virtual co-embodiment enables two users to share a single avatar in Virtual Reality (VR). During such experiences, the illusion of shared motion control can break during joint-action activities, highlighting the need for position-aware feedback mechanisms. Drawing on the perceptual crossing paradigm, we explore how haptics can enable non-verbal coordination between co-embodied participants. In a within-subjects study (20 participant pairs), we examined the effects of vibrotactile haptic feedback (None, Present) and avatar control distribution (25-75%, 50-50%, 75-25%) across two VR reaching tasks (Targeted, Free-choice) on participants Sense of Agency (SoA), co-presence, body ownership, and motion synchrony. We found (a) lower SoA in the free-choice with haptics than without, (b) higher SoA during the shared targeted task, (c) co-presence and body ownership were significantly higher in the free-choice task, (d) players hand motions synchronized more in the targeted task. We provide cautionary considerations when including haptic feedback mechanisms for avatar co-embodiment experiences.

ShareYourReality: Investigating Haptic Feedback and Agency in Virtual Avatar Co-embodiment

TL;DR

Drawing on the perceptual crossing paradigm, how haptics can enable non-verbal coordination between co-embodied participants is explored and cautionary considerations when including haptic feedback mechanisms for avatar co-embodiment experiences are provided.

Abstract

Virtual co-embodiment enables two users to share a single avatar in Virtual Reality (VR). During such experiences, the illusion of shared motion control can break during joint-action activities, highlighting the need for position-aware feedback mechanisms. Drawing on the perceptual crossing paradigm, we explore how haptics can enable non-verbal coordination between co-embodied participants. In a within-subjects study (20 participant pairs), we examined the effects of vibrotactile haptic feedback (None, Present) and avatar control distribution (25-75%, 50-50%, 75-25%) across two VR reaching tasks (Targeted, Free-choice) on participants Sense of Agency (SoA), co-presence, body ownership, and motion synchrony. We found (a) lower SoA in the free-choice with haptics than without, (b) higher SoA during the shared targeted task, (c) co-presence and body ownership were significantly higher in the free-choice task, (d) players hand motions synchronized more in the targeted task. We provide cautionary considerations when including haptic feedback mechanisms for avatar co-embodiment experiences.
Paper Structure (42 sections, 1 equation, 10 figures, 2 tables)

This paper contains 42 sections, 1 equation, 10 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Background and related Work
  3. Virtual avatar co-embodiment and the Sense of Agency
  4. Avatar co-embodiment control sharing techniques
  5. Haptics for virtual co-embodied experiences
  6. Perceptual crossing paradigm for enhancing social coordination
  7. Methods
  8. Study design
  9. Protocol
  10. Joint action reaching tasks
  11. Training
  12. Task 1: Targeted
  13. Task 2: Free-choice
  14. Measures
  15. Objective measures
  16. ...and 27 more sections

Figures (10)

  • Figure 1: Illustration of the weighted average virtual co-embodiment method, where the motion of the shared avatar (center) is generated by taking the weighted average of the motion of User 1 (left) and User 2 (right)
  • Figure 2: Diagram illustrating the different phases of the Study procedure, along with textual labels explaining each component
  • Figure 3: First-person perspective of cube interaction in the targeted task
  • Figure 4: First-person perspective of cube interaction in the free-choice task
  • Figure 5: Waveforms of four vibration patterns used in pre-study (created in Unreal Engine): Intermittent (top left), Sinusoidal (top right), Heartbeat (bottom left) and Constant (bottom right)
  • ...and 5 more figures