Ambient, On-Body, and Implantable Monitoring Technologies to Assess Dietary Behavior

  • Oliver Amft


Self-reports are frequently used in coaching programs on dietary behavior since they provide information on time of food consumption, food types, and amounts in the temporal resolution of individual meal and snack intakes. However, the accuracy of self-reports is influenced by the respondent’s motivation, memorizing, and literate capabilities. The manual labor to complete reports cannot be sustained for several weeks and months, as it would be needed for adequate diet coaching. Computer-based solutions have been developed to reduce the respondent’s effort in filling forms. More recently, sensor-based monitoring approaches were developed, referred to as Automatic Dietary Monitoring (ADM), which target to eliminate manual intake recording entirely. This chapter introduces a technology-oriented taxonomy of dietary behavior assessments. Sensing and information technology concepts are reviewed that have been demonstrated or are applicable for dietary behavior assessment in monitoring programs and out-of-lab studies. The information provided by these monitoring technologies is categorized in four dietary monitoring dimensions: intake schedule, eating microstructure, meal composition and preparation, and consumed food amount. ADM-based solutions were grouped according to fundamental properties, in on-body, implantable, and ambient and installed technologies. On-body and implantable monitoring technologies are particularly applicable to derive eating microstructure information, whereas ambient monitoring techniques are beneficial in assessing food preparation, up to estimation of calorie and biomarker content. ADM can effectively eliminate respondent effort for intake recording and improve information quality and detail, as confirmed in initial focused studies. While ADM-based solutions are currently limited to monitoring individual dietary behavior dimensions only, further research is expected to broaden their application and integrating them with computer-based manual monitoring. A configuration of ADM techniques according to the specific monitoring goal will enable long-term diet coaching programs outside laboratories to address various diet-related diseases.


Smart Card Dietary Behavior Food Amount Monitoring Technology Smart Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Automatic Dietary Monitoring






Personal Digital Assistant




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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.ACTLab, Signal Processing Systems, Faculty of Electrical EngineeringEindhoven University of TechnologyMB EindhovenThe Netherlands

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