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VRsneaky: Increasing Presence in VR Through Gait-Aware Auditory Feedback

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Published:02 May 2019Publication History

ABSTRACT

While Virtual Reality continues to increase in fidelity, it remains an open question how to effectively reflect the user's movements and provide congruent feedback in virtual environments. We present VRsneaky, a system for producing auditory movement feedback, which helps participants orient themselves in a virtual environment by providing footstep sounds. The system reacts to the user's specific gait features and adjusts the audio accordingly. In a user study with 28 participants, we found that VRsneaky increases users' sense of presence as well as awareness of their own posture and gait. Additionally, we find that increasing auditory realism significantly influences certain characteristics of participants' gait. Our work shows that gait-aware audio feedback is a means to increase presence in virtual environments. We discuss opportunities and design requirements for future scenarios where users walk through immersive virtual worlds.

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References

  1. Elena Azañón, Luigi Tamè, Angelo Maravita, Sally A Linkenauger, Elisa R Ferrè, Ana Tajadura-Jiménez, and Matthew R Longo. 2016. Multimodal contributions to body representation. Multisensory Research 29, 6--7 (2016), 635--661.Google ScholarGoogle ScholarCross RefCross Ref
  2. Ann Blandford, Dominic Furniss, and Stephann Makri. 2016. Qualitative HCI research: Going behind the scenes. Synthesis Lectures on Human-Centered Informatics 9, 1 (2016), 1--115. VRsneaky: Gait-Aware Auditory Feedback in Virtual Reality CHI 2019, May 4--9, 2019, Glasgow, Scotland Uk Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Yannic Boysen, Malte Husung, Timo Mantei, Lisa-Maria Müller, Joshua Schimmelpfennig, Lukas Uzolas, and Eike Langbehn. 2018. Scale & Walk: Evaluation von skalierungsbasierten Interaktionstechniken zur natürlichen Fortbewegung in VR. Mensch und Computer 2018Tagungsband (2018).Google ScholarGoogle Scholar
  4. Maureen K Holden. 2005. Virtual environments for motor rehabilitation. Cyberpsychology & behavior 8, 3 (2005), 187--211.Google ScholarGoogle Scholar
  5. Behrang Keshavarz, Bernhard E Riecke, Lawrence J Hettinger, and Jennifer L Campos. 2015. Vection and visually induced motion sickness: how are they related? Frontiers in psychology 6 (2015), 472.Google ScholarGoogle Scholar
  6. Konstantina Kilteni, Ilias Bergstrom, and Mel Slater. 2013. Drumming in immersive virtual reality: the body shapes the way we play. IEEE Transactions on Visualization & Computer Graphics 4 (2013), 597--605. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Ralph J Lamson. 2002. Virtual reality immersion therapy for treating psychological, psychiatric, medical, educational and self-help problems. US Patent 6,425,764.Google ScholarGoogle Scholar
  8. Phil Lopes, Antonios Liapis, and Georgios N Yannakakis. 2017. Modelling affect for horror soundscapes. IEEE Transactions on Affective Computing (2017).Google ScholarGoogle Scholar
  9. MP Murray, RC Kory, and SB Sepic. 1970. Walking patterns of normal women. Archives of physical medicine and rehabilitation 51, 11 (November 1970), 637--650. http://europepmc.org/abstract/MED/5501933Google ScholarGoogle Scholar
  10. Melissa P Murray, A B Drought, and R C Kory. 1964. Walking Patterns of Normal Men. The Journal of bone and joint surgery. American volume 46 (1964), 335--60.Google ScholarGoogle Scholar
  11. Juhani Paasonen, Aleksandr Karapetyan, Jan Plogsties, and Ville Pulkki. 2017. Proximity of Surfaces-Acoustic and Perceptual Effects. Journal of the Audio Engineering Society 65, 12 (2017), 997--1004.Google ScholarGoogle ScholarCross RefCross Ref
  12. Concepción Perpiñá, Cristina Botella, R Baños, H Marco, M Alcañiz, and Soledad Quero. 1999. Body image and virtual reality in eating disorders: is exposure to virtual reality more effective than the classical body image treatment? CyberPsychology & Behavior 2, 2 (1999), 149-- 155.Google ScholarGoogle ScholarCross RefCross Ref
  13. Iana Podkosova, Michael Urbanek, and Hannes Kaufmann. 2016. A Hybrid Sound Model for 3D Audio Games with Real Walking. In Proceedings of the 29th International Conference on Computer Animation and Social Agents (CASA '16). ACM, New York, NY, USA, 189--192. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Maria V Sanchez-Vives and Mel Slater. 2005. From presence to consciousness through virtual reality. Nature Reviews Neuroscience 6, 4 (2005), 332.Google ScholarGoogle ScholarCross RefCross Ref
  15. G Serafin and S Serafin. 2004. Sound design to enhance presence in photorealistic virtual reality. Georgia Institute of Technology.Google ScholarGoogle Scholar
  16. Stefania Serafin, Luca Turchet, and Rolf Nordahl. 2009. Extraction of ground reaction forces for real-time synthesis of walking sounds. Proc. Audiomostly (2009).Google ScholarGoogle Scholar
  17. Mel Slater. 2018. Immersion and the illusion of presence in virtual reality. British Journal of Psychology (2018).Google ScholarGoogle Scholar
  18. Mel Slater and Maria V Sanchez-Vives. 2016. Enhancing our lives with immersive virtual reality. Frontiers in Robotics and AI 3 (2016), 74.Google ScholarGoogle ScholarCross RefCross Ref
  19. Mel Slater, Martin Usoh, and Anthony Steed. 1995. Taking steps: the influence of a walking technique on presence in virtual reality. ACM Transactions on Computer-Human Interaction (TOCHI) 2, 3 (1995), 201--219. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Hyungki Son, Hyunjae Gil, Sangkyu Byeon, Sang-Youn Kim, and Jin Ryong Kim. 2018. RealWalk: Feeling Ground Surfaces While Walking in Virtual Reality. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (CHI EA '18). ACM, New York, NY, USA, Article D400, 4 pages. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Misha Sra and Chris Schmandt. 2015. MetaSpace II: Object and fullbody tracking for interaction and navigation in social VR. arXiv preprint arXiv:1512.02922 (2015).Google ScholarGoogle Scholar
  22. Ana Tajadura-Jiménez, Maria Basia, Ophelia Deroy, Merle Fairhurst, Nicolai Marquardt, and Nadia Bianchi-Berthouze. 2015. As Light As Your Footsteps: Altering Walking Sounds to Change Perceived Body Weight, Emotional State and Gait. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). ACM, New York, NY, USA, 2943--2952. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Luca Turchet, Stefania Serafin, Smilen Dimitrov, and Rolf Nordahl. 2010. Physically based sound synthesis and control of footsteps sounds. In Proceedings of digital audio effects conference, Vol. 11.Google ScholarGoogle Scholar
  24. Graham Wilson, Mark McGill, Matthew Jamieson, Julie R. Williamson, and Stephen A. Brewster. 2018. Object Manipulation in Virtual Reality Under Increasing Levels of Translational Gain. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, Article 99, 13 pages. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Bob G. Witmer, Christian J. Jerome, and Michael J. Singer. 2005. The Factor Structure of the Presence Questionnaire. Presence: Teleoperators and Virtual Environments 14, 3 (June 2005), 298--312. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Bob G. Witmer and Michael J. Singer. 1998. Measuring Presence in Virtual Environments: A Presence Questionnaire. Presence: Teleoperators and Virtual Environments 7, 3 (June 1998), 225--240. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Jacob O. Wobbrock, Leah Findlater, Darren Gergle, and James J. Higgins. 2011. The Aligned Rank Transform for Nonparametric Factorial Analyses Using Only Anova Procedures. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '11). ACM, New York, NY, USA, 143--146. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Ting Zhang, George D Fulk, Wenlong Tang, and Edward S Sazonov. 2013. Using decision trees to measure activities in people with stroke. In Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE. IEEE, 6337--6340.Google ScholarGoogle ScholarCross RefCross Ref

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          cover image ACM Conferences
          CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
          May 2019
          9077 pages
          ISBN:9781450359702
          DOI:10.1145/3290605

          Copyright © 2019 ACM

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          Publication History

          • Published: 2 May 2019

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          CHI '19 Paper Acceptance Rate703of2,958submissions,24%Overall Acceptance Rate6,199of26,314submissions,24%

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