The aim of the study is the modeling of movement and eating behavior, i.e. the identification of types of movement and eating behavior, as well as the quantification of movement intensity or energy consumption, from high-resolution accelerometry data recorded by wearables or smartwatches. In order to develop and validate machine learning models, 600 participants will be recruited, this will be made up of 150 adults in each of four centres, and they will be required to wear a range of state-of-the-art accelerometer devices including wearables for 7 days. Both physical and eating behaviours will be labelled using feedback from event-triggered and random surveys (i.e. Ecological Momentary Assessment) questions. This will lead to the development of an integrated data collection and processing infrastructure.

This page will describe what is required of participants who take part in the study.

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