Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
10-2020
Abstract
Recent research has identified a few design flaws in popular mobile health (mHealth) applications for promoting healthy eating lifestyle, such as mobile food journals. These include tediousness of manual food logging, inadequate food database coverage, and a lack of healthy dietary goal setting. To address these issues, we present Foodbot, a chatbot-based mHealth application for goal-oriented just-in-time (JIT) healthy eating interventions. Powered by a large-scale food knowledge graph, Foodbot utilizes automatic speech recognition and mobile messaging interface to record food intake. Moreover, Foodbot allows users to set goals and guides their behavior toward the goals via JIT notification prompts, interactive dialogues, and personalized recommendation. Altogether, the Foodbot framework demonstrates the use of open-source data, tools, and platforms to build a practical mHealth solution for supporting healthy eating lifestyle in the general population.
Keywords
mHealth, chatbot, diet, self-tracking, food journal, goal-setting, just-in-time intervention, food recommendation, knowledge graph
Discipline
Artificial Intelligence and Robotics | Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
PervasiveHealth'20: Proceedings of the 14th EAI International Conference on Pervasive Computing Technologies for Healthcare
First Page
436
Last Page
439
ISBN
9781450375320
Identifier
10.1145/3421937.3421960
Publisher
ACM
City or Country
New York
Citation
PRASETYO, Philips Kokoh; ACHANANUPARP, Palakorn; and LIM, Ee-peng.
Foodbot: A goal-oriented just-in-time healthy eating interventions chatbot. (2020). PervasiveHealth'20: Proceedings of the 14th EAI International Conference on Pervasive Computing Technologies for Healthcare. 436-439.
Available at: https://ink.library.smu.edu.sg/sis_research/5347
Copyright Owner and License
LARC and Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3421937.3421960