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Mindful Eating
Behavior tracking technology (e.g., step count and food intake) is becoming increasingly popular due to its potential to improve the users' behaviors. With this trend, researchers are exploring new tools to help individuals achieve mindful eating. Thus far, we have explored a variety of ways to design novel interactive techniques to regulate eating habits by increased mindfulness. We systematically reviewed existing digital interventions and persuasive technology for improving the way one eats. Further, based on this review, we generated a design framework for designers of eating intervention technologies. The developed framework was validated through a parallel analysis, and tested in a design brainstorming session. Based on this framework, a smart utensil prototype was developed to detect excessively rapid eating behavior. This smart utensil or a smart fork is a prototype designed to detect eating movements, and estimate the weight of each bite. As a result, our smart fork can recognize when a user is eating too quickly or too slowly. As a next step, we plan to explore novel feedback mechanisms for fast eaters in real life setting.
Project Publications
A Comparison between Audio and IMU data to Detect Chewing Events Based on an Earable Device
Roya Lotfi, George Tzanetakis, Rasit Eskicioglu, and Pourang Irani. 2020. A Comparison between Audio and IMU data to Detect Chewing Events Based on an Earable Device. In 11th Augmented Human International Conference (AH ’20), May 27–29, 2020, Winnipeg, MB, Canada. ACM, New York, NY, USA, 8pages. https://doi.org/10.1145/3396339.3396362
A Smart Utensil for Detecting Food Pick-Up Gesture and Amount While Eating
Zuoyi Zhang, Huizhe Zheng, Sawyer Rempel, Kenny Hong, Teng Han, Yumiko Sakamoto, and Pourang Irani. 2020. A smart utensil for detecting food pick-up gesture and amount while eating. In Proceedings of the 11th Augmented Human International Conference (AH '20). Association for Computing Machinery, New York, NY, USA, Article 2, 1–8. DOI:https://doi.org/10.1145/3396339.3396361 (3rd best paper award)
Design to Eat Smart! A Design Framework for Pervasive Interventions
Zuoyi Zhang, Teng Han, John Swystun, Yumiko Sakamoto, and Pourang Irani. 2020. Design to Eat Smart! A Design Framework for Pervasive Interventions of Eating Habits. To appear at Pervasive Health 2020.
Applying a Pneumatic Interface to Intervene with Rapid Eating Behaviour
Zhang Z, Kim J, Sakamoto Y, Han T, Irani P. Applying a Pneumatic Interface to Intervene with Rapid Eating Behaviour. Stud Health Technol Inform. 2019;257 513-519. PMID: 30741249.
