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

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

doi:10.1145/3281505.3281573

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

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

Graduate School of Media Design

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

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 language	English
Title of host publication	Proceedings - VRST 2018
Subtitle of host publication	24th ACM Symposium on Virtual Reality Software and Technology
Editors	Stephen N. Spencer
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450360869
DOIs	https://doi.org/10.1145/3281505.3281573
Publication status	Published - 2018 Nov 28
Event	24th ACM Symposium on Virtual Reality Software and Technology, VRST 2018 - Tokyo, Japan Duration: 2018 Nov 28 → 2018 Dec 1

Other

Other	24th ACM Symposium on Virtual Reality Software and Technology, VRST 2018
Country	Japan
City	Tokyo
Period	18/11/28 → 18/12/1

Keywords

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

ASJC Scopus subject areas

Software

Access to Document

10.1145/3281505.3281573

Fingerprint Dive into the research topics of 'Hand motion prediction for just-in-time thermo-haptic feedback'. Together they form a unique fingerprint.

Cite this

Hand motion prediction for just-in-time thermo-haptic feedback. / Chernyshov, George; Ragozin, Kirill; Caremel, Cedric; Kunze, Kai Steven.

Proceedings - VRST 2018: 24th ACM Symposium on Virtual Reality Software and Technology. ed. / Stephen N. Spencer. Association for Computing Machinery, 2018. 3281573.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chernyshov, G, Ragozin, K, Caremel, C & Kunze, KS 2018, Hand motion prediction for just-in-time thermo-haptic feedback. in SN Spencer (ed.), Proceedings - VRST 2018: 24th ACM Symposium on Virtual Reality Software and Technology., 3281573, Association for Computing Machinery, 24th ACM Symposium on Virtual Reality Software and Technology, VRST 2018, Tokyo, Japan, 18/11/28. https://doi.org/10.1145/3281505.3281573

@inproceedings{9f8abc0852674ebc8136bd3fa6d0c385,

title = "Hand motion prediction for just-in-time thermo-haptic feedback",

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.",

keywords = "Haptic feedback, Machine learning, Motion prediction, Neural networks, Thermal feedback, Virtual reality",

author = "George Chernyshov and Kirill Ragozin and Cedric Caremel and Kunze, {Kai Steven}",

year = "2018",

month = nov,

day = "28",

doi = "10.1145/3281505.3281573",

language = "English",

editor = "Spencer, {Stephen N.}",

booktitle = "Proceedings - VRST 2018",

publisher = "Association for Computing Machinery",

note = "24th ACM Symposium on Virtual Reality Software and Technology, VRST 2018 ; Conference date: 28-11-2018 Through 01-12-2018",

}

TY - GEN

T1 - Hand motion prediction for just-in-time thermo-haptic feedback

AU - Chernyshov, George

AU - Ragozin, Kirill

AU - Caremel, Cedric

AU - Kunze, Kai Steven

PY - 2018/11/28

Y1 - 2018/11/28

N2 - 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.

AB - 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.

KW - Haptic feedback

KW - Machine learning

KW - Motion prediction

KW - Neural networks

KW - Thermal feedback

KW - Virtual reality

UR - http://www.scopus.com/inward/record.url?scp=85060906705&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85060906705&partnerID=8YFLogxK

U2 - 10.1145/3281505.3281573

DO - 10.1145/3281505.3281573

M3 - Conference contribution

AN - SCOPUS:85060906705

BT - Proceedings - VRST 2018

A2 - Spencer, Stephen N.

PB - Association for Computing Machinery

T2 - 24th ACM Symposium on Virtual Reality Software and Technology, VRST 2018

Y2 - 28 November 2018 through 1 December 2018

ER -