June 2008: New publication: Gesture Spotting with Body-Worn Inertial Sensors to Detect User Activities. Pattern Recognition, 2008, 41(6), 2010-2024.
Feb 2008: New publication: Recognition of dietary activity events using on-body sensors. Artificial Intelligence in Medicine, 2008, 42(2), 121-136.
Jan 2008: An update of the ADM research projects pages is out, see here.
Nov 2007: The paper Automatic Identification of Temporal Sequences in Chewing Sounds was published and presented at IEEE BIBM 2007.
Sep 2007: First workshop on Nutrition and Public Health (e-Nutrition 2007) successfully concluded.
Project Start: August 2004
Appropriate nutrition is a major aspect of a healthy lifestyle. Worldwide, a considerable number of life-years is lost due to the increasing prevalence of overweight, obesity and related chronic diseases. We believe that novel ubiquitous sensing solutions for continuous activity monitoring are vital cornerstones for diet behaviour coaching in risk groups and reduce diet-related diseases.
Current monitoring solutions require the user/patient to fill in questionnaires for all food consumed throughout the day. This is laborious and known to be very inaccurate. We develop and test solutions that do not require manual logging, hence Automatic Dietary Monitoring.
For this purpose we deploy sensors of different modalities that can be worn at the body or integrated into clothing. Pattern recognition methods are used to extract information and infer diet-related activities and consumed foods. Moreover we analyse sensor data for information related to the eating microstructure. This can be used to broaden the understanding of malnutrition.
We were able to demonstrate the feasibility of Automated Dietary Monitoring in a set of studies using on-body sensors and adapted pattern recognition methods. To capture the complex (partly unconscious) behavioural process we decomposed eating activities into different domains:
An intake cycle model was defined and applied to segment feeding (intake) cycles, obtain insight on the eating process and determine its temporal structure. More...
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