TeslaTouch: electrovibration for touch surfaces
By Olivier Bau, Ivan Poupyrev, Ali Israr, Chris Harrison. ACM Symposium on User Interface Software and Technology, 2010
684 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Human-Computer Interaction
View Paper: https://www.semanticscholar.org/paper/1797408073eb83970dfd026b911e2b213d03cc04
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In Cognitive Neuroscience
In Human-Computer Interaction
Citations in the corpus
- Touché: enhancing touch interaction on humans, screens, liquids, and everyday objects (2012, background): “See [2, 6, 21, 24, 25, 27, 44] for a subset of previous work on touch.”
- UltraHaptics: multi-point mid-air haptic feedback for touch surfaces (2013, methodology): “Frequency JND (just-noticeable-difference) thresholds have found that the hand is able to discriminate between 12% to 25% difference in frequencies, and the amount of this difference depends on the reference frequency [2].”
- Haptics: The Present and Future of Artificial Touch Sensation (2018, background): “Another way to modulate friction uses changing electrostatic forces (109, 130) (Figure 8b).”
- Tactile brush: drawing on skin with a tactile grid display (2011, background): “First is the design of actuation technologies and control techniques needed to produce a micro-structure of tactile sensations, e.g., vibration [27], surface roughness [5], skin stretch [23], rotational profiles [25] and others.”
- NormalTouch and TextureTouch: High-fidelity 3D Haptic Shape Rendering on Handheld Virtual Reality Controllers (2016, neutral): “Teslatouch [3] applied electrovibration to the surface of a handheld screen to programmatically vary surface friction during touch interactions.”