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Evaluating discrete viewpoint control to reduce cybersickness in virtual reality

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Abstract

Cybersickness in virtual reality (VR) is an ongoing problem, despite recent advances in head-mounted displays (HMDs). Discrete viewpoint control techniques have been recently used by some VR developers to combat cybersickness. Discrete viewpoint techniques rely on reducing optic flow via inconsistent displacement, to reduce cybersickness when using stationary HMD-based VR systems. However, reports of their effectiveness are mostly anecdotal. We experimentally evaluate two discrete movement techniques; we refer to as rotation snapping and translation snapping. We conducted two experiments measuring participant cybersickness levels via the widely used simulator sickness questionnaire (SSQ), as well as user-reported levels of nausea, presence, and objective error rates. Our results indicate that both rotation snapping and translation snapping significantly reduced SSQ by 40% for rotational viewpoint movement, and 50% for translational viewpoint movement. They also reduced participant nausea levels, especially with longer VR exposure. Presence levels, error rates, and performance were not significantly affected by either technique.

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Notes

  1. http://www.croteam.com/.

  2. http://www.capcom.com/.

  3. https://gaming.youtube.com/game/UCs9XYBocLgnrQIuWKf0zuCw.

  4. https://store.steampowered.com/app/344180/Valiant/.

  5. http://www.vr-bits.com/.

  6. https://www.youtube.com/watch?v=vVVdoquKhO8&t=15s.

  7. With 6 students from laboratory (age from 20 to 34).

  8. https://docs.unity3d.com/ScriptReference/AI.NavMeshAgent.html.

  9. We tested several different distances with 6 members in the laboratory to select four different jump distances.

  10. We also normalized the scores with standard score formula: \( {\text{Time}}\;{\text{score}} = \frac{{{\text{calculated}}\;{\text{time}} - u}}{\sigma } \); where µ is the mean and σ is the standard deviation of each jump distance group. The result was the same for both formulas. By doing this, we ensure that scores are normalized based on jump distance average score, since otherwise, the 2 m jump distance would always have the best score.

  11. One jump occurs with each click; hence, the number of clicks can be calculated from the traveled distance. For example, traveling 193 m with the 1 m jump distance required 193 clicks.

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Authors and Affiliations

  1. School of Computer Science, Carleton University, Ottawa, ON, Canada

    Yasin Farmani

  2. School of Information Technology, Carleton University, Ottawa, ON, Canada

    Robert J. Teather

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  1. Yasin Farmani
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  2. Robert J. Teather
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Correspondence to Yasin Farmani.

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Farmani, Y., Teather, R.J. Evaluating discrete viewpoint control to reduce cybersickness in virtual reality. Virtual Reality 24, 645–664 (2020). https://doi.org/10.1007/s10055-020-00425-x

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