The diet-aware dining table: Observing dietary behaviors over a tabletop surface

Keng Hao Chang*, Shih Yen Liu, Hao Hua Chu, Jane Yung Jen Hsu, Cheryl Chen, Tung Yun Lin, Chieh Yu Chen, Polly Huang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

86 Scopus citations


We are what we eat. Our everyday food choices affect our long-term and short-term health. In the traditional health care, professionals assess and weigh each individual's dietary intake using intensive labor at high cost. In this paper, we design and implement a diet-aware dining table that can track what and how much we eat. To enable automated food tracking, the dining table is augmented with two layers of weighing and RFID sensor surfaces. We devise a weight-RFID matching algorithm to detect and distinguish how people eat. To validate our diet-aware dining table, we have performed experiments, including live dining scenarios (afternoon tea and Chinese-style dinner), multiple dining participants, and concurrent activities chosen randomly. Our experimental results have shown encouraging recognition accuracy, around 80%. We believe monitoring the dietary behaviors of individuals potentially contribute to diet-aware healthcare.

Original languageEnglish
Title of host publicationPervasive Computing - 4th International Conference, PERVASIVE 2006, Proceedings
PublisherSpringer Verlag
Number of pages17
ISBN (Print)3540338942, 9783540338949
StatePublished - 2006
Externally publishedYes
Event4th International Conference on Pervasive Computing, PERVASIVE 2006 - Dublin, Ireland
Duration: 07 05 200610 05 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3968 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th International Conference on Pervasive Computing, PERVASIVE 2006


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