Integrating electronic components into deformable objects based on user interaction data
Name
2019-tei-deformable-objects-paper.pdf
Description
Accepted version
Size
7.01 MB
Format
Adobe PDF
Checksum (MD5)
7007339013885bbc8d02fc99a558c77c
Author(s)
Worgan, Paul
Reuss, Kevin
Mueller, Stefanie
Date Issued
March 2019
Journal
Proceedings of the Thirteenth International Conference on Tangible, Embedded, and Embodied Interaction
Publisher
Association for Computing Machinery
Citation
Worgan, Paul, Kevin Reuss and Stefanie Mueller. "Integrating electronic components into deformable objects based on user interaction data." In Proceedings of the Thirteenth International Conference on Tangible, Embedded, and Embodied Interaction, TEL'19, Tempe, Arizona, USA, March 17-20, 2019, Pages 345-350.
Version
Author's final manuscript
Abstract
A key challenge when designing deformable user interfaces is the integration of rigid electronic components with the soft deformable device. In this paper, we propose to place electronic components based on how the user is interacting with the device, i.e., in which way the device is being deformed when the user performs gestures. To identify optimum locations for placing electronic components, we developed a design tool that takes as input a 3D model of the deformable device and a set of captured user gestures. It then visualizes the stress distribution resulting from the gestures applied to the deformable device and suggests where not to place components because the location is highly deformed when users interact (e.g., a rigid battery that would constraint interaction); or alternatively where to place components to sense deformation more accurately (e.g., a bend sensor to detect a specific gesture) and efficiently (e.g., an energy harvesting component). We evaluated our approach by collecting interaction data from 12 users across three deformable devices (a watch, a camera, and a mouse) and applied the resulting stress distributions to the placement of selected electronic components.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3294109.3295629
