Self-reports are frequently used in coaching programmes on dietary behaviour since they provide information on time of food consumption, food types, and amounts in the temporal resolution of individual meal and snack intakes. However, accuracy of self-reports is influenced by to the respondent's motivation, memorising, and literate capabilities. The manual labour 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 behaviour assessments. Sensing and information technology concepts are reviewed that have been demonstrated, or are applicable for dietary behaviour assessment in monitoring programs and out-of-lab studies. The information provided by these monitoring technologies is categorised in four dietary monitoring dimensions: intake schedule, eating microstructure, meal composition and preparation, and consumed food amount.
|Title of host publication||International handbook of behavior, diet and nutrition|
|Editors||V.R. Preedy, R.R. Watson, C.R. Martin|
|Place of Publication||Berlin|
|Number of pages||3667|
|Publication status||Published - 2011|
Amft, O. D. (2011). Ambient, on-body, and implantable monitoring technologies to assess dietary behaviour. In V. R. Preedy, R. R. Watson, & C. R. Martin (Eds.), International handbook of behavior, diet and nutrition (pp. 3507-3526). Springer. https://doi.org/10.1007/978-0-387-92271-3_219