Lin, YJ; Punpongsanon, P; Wen, X; Iwai, D; Sato, K; Obrist, M; Mueller, S; (2020) FoodFab: Creating Food Perception Illusions using Food 3D Printing. In: CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery (ACM): Honolulu, HI, USA.

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Abstract

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.

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