File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher

OakleyIan

Oakley, Ian
Interactions Lab.
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Interaction on the edge: Offset sensing for small devices

Author(s)
Oakley, IanLee, Doyoung
Issued Date
2014-04-26
DOI
10.1145/2556288.2557138
URI
https://scholarworks.unist.ac.kr/handle/201301/46645
Fulltext
http://dl.acm.org/citation.cfm?doid=2556288.2557138
Citation
32nd Annual ACM Conference on Human Factors in Computing Systems, CHI 2014, pp.169 - 178
Abstract
The touch screen interaction paradigm, currently dominant in mobile devices, begins to fail when very small systems are considered. Specifically, "fat fingers", a term referring to the fact that users' extremities physically obstruct their view of screen content and feedback, become particularly problematic. This paper presents a novel solution for this issue based on sensing touches to the perpendicular edges of a device featuring a front-mounted screen. The use of such offset contact points ensures that both a user's fingers and the device screen remain clearly in view throughout a targeting operation. The configuration also supports a range of novel interaction scenarios based on the touch, grip and grasp patterns it affords. To explore the viability of this concept, this paper describes EdgeTouch, a small (6 cm) hardware prototype instantiating this multi-touch functionality. User studies characterizing targeting performance, typical user grasps and exploring input affordances are presented. The results show that targets of 7.5-22.5 degrees in angular size are acquired in 1.25-1.75 seconds and with accuracy rates of 3%-18%, promising results considering the small form factor of the device. Furthermore, grasps made with between two and five fingers are robustly identifiable. Finally, we characterize the types of input users envisage performing with EdgeTouch, and report occurrence rates for key interactions such as taps, holds, strokes and multi-touch and compound input. The paper concludes with a discussion of the interaction scenarios enabled by offset sensing.
Publisher
32nd Annual ACM Conference on Human Factors in Computing Systems, CHI 2014

qrcode

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.