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AnyButton: unpowered, modeless and highly available mobile input using unmodified clothing buttons

Published: 07 March 2014 Publication History

Abstract

This paper presents wearable opportunistic controls using unmodified clothing buttons. Buttons are commonly sewn on formal clothing and often came with multiple duplicates. In this paper, we turn passive buttons into dial widgets. Each button provides simple input modalities (e.g., tap and spin inputs). Multiple buttons allow for modeless and rich interactions. We present AnyButton, a wearable motion-sensor set, allowing for transferring buttons on clothing into mobile input on the move. Our prototype consists of three motion sensors attached on the index fingernail, the wrist, and the elbow. We interpret which button is under user interaction according to the wrist and elbow orientations, and how the button in the user's finger pinches being operated according to the motions on the fingertips. Each button allows for partial tap, discrete spin and dwell spin inputs. By distributing interface to the buttons, applications such as music players and call centers can use opportunistic clothing buttons as wearable controls.

References

[1]
Cheng, K.-Y., Liang, R.-H., Chen, B.-Y., Laing, R.-H., and Kuo, S.-Y iCon: utilizing everyday objects as additional, auxiliary and instant tabletop controllers. In Proc. ACM CHI '10 (2010), 1155--1164.
[2]
Henderson, S. J., and Feiner, S. Opportunistic controls: leveraging natural affordances as tangible user interfaces for augmented reality. In Proc. ACM VRST '08 (2008), 211--218.

Cited By

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  • (2020)A Systematic Study of Unsupervised Domain Adaptation for Robust Human-Activity RecognitionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33809854:1(1-30)Online publication date: 14-Sep-2020

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cover image ACM Other conferences
AH '14: Proceedings of the 5th Augmented Human International Conference
March 2014
249 pages
ISBN:9781450327619
DOI:10.1145/2582051
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 March 2014

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AH '14
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  • MEET IN KOBE 21st Century

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Overall Acceptance Rate 121 of 306 submissions, 40%

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View all
  • (2020)A Systematic Study of Unsupervised Domain Adaptation for Robust Human-Activity RecognitionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33809854:1(1-30)Online publication date: 14-Sep-2020

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