A Review of Behavioral Closed-Loop Paradigm from Sensing to Intervention for Ingestion Health

Jun Fang; Yanuo Zhou; Ka I Chan; Jiajin Li; Zeyi Sun; Zhengnan Li; Zicong Fu; Hongjing Piao; Haodong Xu; Yuanchun Shi; Yuntao Wang

arXiv · 2505.03185

A Review of Behavioral Closed-Loop Paradigm from Sensing to Intervention for Ingestion Health

Jun Fang·Yanuo Zhou·Ka I Chan·Jiajin Li·Zeyi Sun·Zhengnan Li·Zicong Fu·Hongjing Piao·Haodong Xu·Yuanchun Shi·Yuntao Wang

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Abstract

Ingestive behavior plays a critical role in health, yet many existing interventions remain limited to static guidance or manual self-tracking. With the increasing integration of sensors, context-aware computing, and perceptual computing, recent systems have begun to support closed-loop interventions that dynamically sense user behavior and provide feedback during or around ingestion episodes. In this survey, we review 136 studies that leverage sensor-enabled or interaction-mediated approaches to influence ingestive behavior. We propose a behavioral closed-loop paradigm rooted in context-aware computing and inspired by HCI behavior change frameworks, comprising four components: target behaviors, sensing modalities, reasoning and intervention strategies. A taxonomy of sensing and intervention modalities is presented, organized along human- and environment-based dimensions. Our analysis also examines evaluation methods and design trends across different modality-behavior pairings. This review reveals prevailing patterns and critical gaps, offering design insights for future adaptive and context-aware ingestion health interventions.

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Jun Fang, Yanuo Zhou, Ka I Chan, Jiajin Li, Zeyi Sun, Zhengnan Li, Zicong Fu, Hongjing Piao, Haodong Xu, Yuanchun Shi, Yuntao Wang. 2025-05-06. A Review of Behavioral Closed-Loop Paradigm from Sensing to Intervention for Ingestion Health. https://arxiv.org/abs/2505.03185

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