enable - Healthy food choices in all stages of life
The number of people with bad nutrition behavior is rising leading to critical long-term health risks for the individual and severe costs for the health system. Current solutions for health interventions suffer from high drop-out rates and are not able to provide predictive or real-time interventions as they build on post input of nutrition or activity data. Thus, new approaches must be found that allow tailored, context-aware, and anticipatory dietary recommendations to engage users into a sustainable behavioral change.
Interdisciplinary research for a healthier diet: enable develops new strategies to provide a healthier diet for people at different stages of their lives (from birth to old age). We carry out interdisciplinary research at the juncture of nutrition science and food technology with information and communication technology and social science. Modern nutrition with convenience foods and a healthy lifestyle do not have to be contradictory - this is what our cluster wants to contribute to. We use modern information and communication technology to introduce consumers to a healthy diet.
The Chair for Information Systems devotes its work to the vision of a Virtual Dietary Advisor (VDA) to enable tailored, context-aware, and anticipatory dietary recommendations in order to sustain and improve healthy eating behavior. By following an iterative Design Science approach, evaluated requirements, methods, algorithms and design principles are developed as the building blocks for a future VDA. Therefore, this project builds on insights gained from the data collected through two apps, APPetite and Nutrilize, which were developed and released during the first funding period of the enable Cluster. Module 1 will develop methods for collecting and analyzing nutrition-relevant data to create comprehensive user profiles. Module 2 will develop advanced algorithms and data models for tailored, context-aware and anticipatory dietary recommendations, utilizing the comprehensive user profiles. Module 3 investigates features of the user interface of a VDA. It focuses on optimal ways of communication between a user and a VDA, such that efforts of usage are limited and recommendations are provided in a context-sensitive and tailored way. Following an iterative Design Science approach, prototypes of the different methods, algorithms and features are developed early and are enhanced according to the insights from the accompanying evaluations.
Digital Twin: towards a rich nutrition-relevant user profile
Algorithms and data-models for modern context-aware nutrition-advice applications
Optimal user interface for a virtual dietary advisor
The results of this Focus Area (requirements, methods, algorithms and design principles) build the foundation for future IT-enabled interventions to improve public health through dietary recommendations that can be scaled to reach a large population.
Technische Universität München, Personalized Nutrition Group (PD Dr. Kurt Gedrich)
The interdisciplinary enable cluster is one of four nutrition research clusters funded by the German Federal Ministry of Education and Research (BMBF).