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 | |
| 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
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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