Duration: 2022 – 2024
Cised team members
Carlos Augusto da Silva Cunha
Ricardo Luís da Costa Gama
Food assumes an increasingly important role in people's lives, and adequate nutrition associated with a healthy lifestyle increases the average life expectancy. To this end, there has been an increase in the number of people whom nutritionists are following to have a food plan suited to their needs, which vary according to each person's goals: from the purely aesthetic component, through the improvement of the quality of life, for professional reasons (such as sportsmen or high competition athletes), even people with special needs, in which a correct diet impacts on the aggravation of previously diagnosed diseases. There are, however, some associated problems that can impact noncompliance with a previously defined meal plan. One of them is defining a food plan made up of foods people don't like. The other relates to real-time notification of the nutritionist of the correct fulfilment of the plan in terms of the proper intake of recommended macronutrients in each meal of the food plan.
Regarding the first, the combination of foods is a factor mainly linked to people's preferences, far beyond the rules of food combinations recommended by nutritionists. Thus, patterns for each individual may vary over time and as a function of other conditions (e.g., temperature, season). People's sensitivity to these combinations is one of the factors responsible for abandoning eating plans and not matching their food tastes. With this work, we intend to develop an Artificial Intelligence model to detect food patterns to adapt a food plan defined by a nutritionist in an evolutionary way and in real-time to allow the correct management of the plan. Thus, it becomes possible to provide a better quality of life to people who need to define food plans in various types of contexts.