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Touché: enhancing touch interaction on humans, screens, liquids, and everyday objects

Sato, Munehiko, Poupyrev, Ivan, Harrison, Chris·2012·Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Abstract

Touché proposes a novel Swept Frequency Capacitive Sensing technique that can not only detect a touch event, but also recognize complex configurations of the human hands and body. Such contextual information significantly enhances touch interaction in a broad range of applications, from conventional touchscreens to unique contexts and materials. For example, in our explorations we add touch and gesture sensitivity to the human body and liquids. We demonstrate the rich capabilities of Touché with five example setups from different application domains and conduct experimental studies that show gesture classification accuracies of 99% are achievable with our technology.

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Metadata

Authors
Sato, M., Poupyrev, I., & Harrison, C.
Venue
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2012-05-05
Pages
483-492
OpenAlex
W2088182082
Cited by
322
References
2
FWCI
23.39
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Touché: enhancing touch interaction on humans, screens, liquids, and everyday objects. https://app.cochat.ai/papers/10.1145/2207676.2207743
The paper
Sato, M., Poupyrev, I., & Harrison, C. (2012). Touché: enhancing touch interaction on humans, screens, liquids, and everyday objects. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/2207676.2207743

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.