Exploring a novel design to support healthy eating

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Zhang, Zuoyi
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Seemingly trivial eating habits, such as eating too fast, have been linked to diverse and rather serious health issues. While technology-mediated interventions have leveraged several strategies to promote healthy dietary habits, designing successful pervasive interventions remains challenging. This thesis first offers three contributions with the aim of assisting in the design of eating interventions: 1) a review of 62 studies which focused on interventions targeting eating habits; 2) a generative design framework with multiple design parameters; and, 3) an exploration of the potential efficacy of the developed framework. These contributions will improve designers’ comprehension and ability to apply current trends and state of the art technologies in the design space. Heightened food intake rates (i.e., eating too fast) are linked to several health concerns such as an elevated risk of obesity or gastritis. In this thesis, a novel smart-eating utensil is proposed, which can potentially increase the users’ awareness of their eating rate by detecting their food pick-up gesture as well as the weight of the food on the utensil before each bite. A proof-of- concept prototype fork with multiple embedded sensors and a processor to collect the eating data was designed and implemented. Following this, a solution was proposed for the food pick-up gesture detection and food amount estimation in each bite. The accuracy of our solution is assessed through ten successful data collection sessions with participants. A low fidelity proof-of-concept prototype device has been developed to demonstrate the feasibility of applying a pneumatically actuated shape-changing interface to embed physical interference into an eating utensil. A high fidelity, self-contained prototype smart fork was built with the ability to detect the food pick up gesture and provide the bending fork feedback to the users. When the fork detects the user’s attempt to pick up food within a short interval following their last food pick-up, the fork bends itself using its mechanical structure, so as the user cannot efficiently pick up food. However, if the user waits a sufficient time before their next food pick-up the fork will not bend, and the user may consume the bite without interference.
Eating detection, Human-computer interaction, Healthy eating, Design framework, Novel feedback, Smart eating utensil
Zuoyi Zhang, Teng Han, John Swystun, Yumiko Sakamoto, and Pourang Irani. “Design to Eat Smart! A Design Framework for Pervasive Interventions of Eating Habits.” In: To appear at PervasiveHealth 2020. 2020.
Zuoyi Zhang, Junhyeok Kim, Yumiko Sakamoto, Teng Han, and Pourang Irani. “Applying a Pneumatic Interface to Intervene with Rapid Eating Behaviour.” In: Studies in health technology and informatics 257 (2019), 513—519. issn: 0926-9630. url: http://europepmc.org/abstract/MED/30741249.
Zuoyi Zhang, Huizhe Zheng, Sawyer Rempel, Kenny Hong, Teng Han, Yumiko Sakamoto, and Pourang Irani. “A Smart Utensil for Detecting Food Pick-up Gesture and Amount While Eating.” In: Proceedings of the 11th Augmented Human International Conference. AH ’20. Winnipeg, Manitoba, Canada: Association for Computing Machinery, 2020. isbn: 9781450377287. doi: 10.1145/3396339.3396361. url: https://doi.org/10.1145/3396339. 3396361.