PROTEIN (PeRsOnalized nutriTion for hEalthy livINg), H2020, DT-SFS-14-2018


Proper nutrition is essential for good health, well-being and the prevention, mitigation or treatment of a number of non-communicable diseases (NCDs). Food is not only a source of calories, but also a complex mixture of dietary chemicals, some of which are directly related to cardiovascular diseases, diabetes, allergies and some types of cancer. Foods, diet and nutritional status, including overweight and obesity, are also associated with elevated blood pressure and blood cholesterol or even resistance to the action of insulin. These conditions are not only risk factors for noncommunicable diseases, but major causes of illness themselves. However, today’s diet is characterized by irregular and poorly balanced meals. Unhealthy eating habits in our daily life are not only risk factors for non-communicable diseases, but also major causes of stress and tiredness, i.e., lack of energy. Knowledge about our dietary habits based on the analysis of diverse types of information, including individual parameters, can contribute greatly towards answering key questions to respond to societal challenges regarding food and health.
Motivated by the aforementioned, the PROTEIN project aims to develop an end-to-end ecosystem that will engage people to a healthy, pleasurable, nutritional and sustainable diet by offering a daily program adapted to their needs and driven by their personal preferences, physical and physiological characteristics as well as their health status. Specifically, the main objective of PROTEIN is to create an ICT-based system for providing personalized nutrition based on the collection and analysis of large volumes of data related to users’ dietary behavioural patterns, physical activity and individual parameters. PROTEIN proposes a radically novel approach to advice and support consumers in everyday living, while ensuring users’ privacy protection i.e., data will be anonymized and securely stored in the Cloud for processing.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 817732.