Hand motion prediction for just-in-time thermo-haptic feedback

George Chernyshov, Kirill Ragozin, Cedric Caremel, Kai Steven Kunze

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents two innovative design solutions for thermal feedback displays in virtual environments. First solution is aiming to eliminate or decrease the time delay between the user action and onset of the thermal feedback using Machine Learning for user motion prediction. Second is the design of compact but efficient water cooling system necessary to provide cold sensations using peltier elements. Presented thermal display is wearable and battery powered.

Original languageEnglish
Title of host publicationProceedings - VRST 2018
Subtitle of host publication24th ACM Symposium on Virtual Reality Software and Technology
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450360869
DOIs
Publication statusPublished - 2018 Nov 28
Event24th ACM Symposium on Virtual Reality Software and Technology, VRST 2018 - Tokyo, Japan
Duration: 2018 Nov 282018 Dec 1

Other

Other24th ACM Symposium on Virtual Reality Software and Technology, VRST 2018
CountryJapan
CityTokyo
Period18/11/2818/12/1

Keywords

  • Haptic feedback
  • Machine learning
  • Motion prediction
  • Neural networks
  • Thermal feedback
  • Virtual reality

ASJC Scopus subject areas

  • Software

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  • Cite this

    Chernyshov, G., Ragozin, K., Caremel, C., & Kunze, K. S. (2018). Hand motion prediction for just-in-time thermo-haptic feedback. In S. N. Spencer (Ed.), Proceedings - VRST 2018: 24th ACM Symposium on Virtual Reality Software and Technology [3281573] Association for Computing Machinery. https://doi.org/10.1145/3281505.3281573