FoodFab: Creating Food Perception Illusions using Food 3D Printing
Name
3313831.3376421.pdf
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28.12 MB
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Adobe PDF
Checksum (MD5)
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Author(s)
Lin, Ying-Ju
Punpongsanon, Parinya
Wen, Xin
Iwai, Daisuke
Sato, Kosuke
Obrist, Marianna
Mueller, Stefanie
Date Issued
April 21, 2020
Journal
Conference on Human Factors in Computing Systems - Proceedings
Publisher
ACM
Citation
Lin, Ying-Ju, Punpongsanon, Parinya, Wen, Xin, Iwai, Daisuke, Sato, Kosuke et al. 2020. "FoodFab: Creating Food Perception Illusions using Food 3D Printing." Conference on Human Factors in Computing Systems - Proceedings.
Version
Final published version
Abstract
© 2020 ACM. Personalization of eating such that everyone consumes only what they need allows improving our management of food waste. In this paper, we explore the use of food 3D printing to create perceptual illusions for controlling the level of perceived satiety given a defined amount of calories. We present FoodFab, a system that allows users to control their food intake through modifying a food's internal structure via two 3D printing parameters: infill pattern and infill density. In two experiments with a total of 30 participants, we studied the effect of these parameters on users' chewing time that is known to affect people's feeling of satiety. Our results show that we can indeed modify the chewing time by varying infill pattern and density, and thus control perceived satiety. Based on the results, we propose two computational models and integrate them into a user interface that simplifies the creation of personalized food structures.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1145/3313831.3376421
