Digital Twin: towards a rich nutrition relevant user profile (FA5 module 1)

Over the last few years, the number of mobile applications and wearables that focus on nutrition and physical activity to improve the lifestyle has risen rapidly. While most of these apps collect a lot of data from the user (diet protocols, water intake, step numbers, sleep patterns, etc.), they hardly use these data. Instead of using these data separately, linking them together can provide valuable personalized insights to adapt dietary recommendations.

This Focus Area 5 deals with the development of methods for collecting and analyzing nutrition-related data in order to create rich user profiles. In other words, the creation of an information base that a later virtual dietary advisor can use to make personalized recommendations. As part of this process, this module builds on connections between different influencing factors and nutritional behavior as well as on the findings from the first funding period of the enable Competence Cluster and examines various possibilities for obtaining the required information, with as little effort as possible from the user.

The results of this module will enable us to gain a better understanding of the nutritional behavior of individual users and thus create the foundation for providing targeted nutritional advice and support.

Our objectives

The aim is to create an information base for a virtual dietary advisor which can provide tailor-made, context-related and forward-looking nutritional recommendations to support and improve healthy eating behavior. Intermediate goals are here

  • provide an overview of necessary information and possible data sources.
  • Develop methods to collect the required information.
  • Develop methods to draw and evaluate relevant conclusions from the collected data.