The high demand for nutritional support applications in the general population can be estimated on the basis of the more than 100,000 health and nutrition apps currently available. The available apps range from diet diaries over calorie counters to diet or meal planners. Existing apps mostly work on the basis of user input, which often has a subjective character in terms of the anthropometric data specifications such as weight, height and body circumference, as well as in terms of the dietary habits of the users.

The use of biosensors to measure a person’s nutritional and health status opens up the possibility to create an objective, evidence-based method for the development of a reliable healthcare app using real data generated by sensors. For this purpose, a pilot study will first generate data from young, healthy volunteers using portable sensors and nutrition protocols that reflect their nutritional and health status. The collected data will then be used in a machine learning process to develop a lifestyle and healthcare app, which will provide the wearer with concrete suggestions based on their individual physiological-medical phenotype for the selection of food and the time of consumption. In a validation study, these sensors are then used for a nutritional intervention with protein-rich foods in >50-year-old subjects. Based on the obtained sensor data, food proposals for various dietary scenarios will be developed.

Current nutritional guides do not include specially designed food components and usually only a limited selection of locally available foods that can be delivered within transport routes. Therefore, as part of the f4f-subproject, the novel foods that are developed and designed within the framework of food4future (f4f) will be added into the food spectrum of the app, thus expanding its offer for an individualized, needs-based diet. The large selection of local foods in the app's food spectrum ensures that the optimal provision of its users can still be guaranteed in spite of the changing globalized markets and environment ("No Land”, “No Trade") without having to resort to exotic, long-distance food.

D. Weber, T. Hening (DIfE)