Adopting the Mediterranean Diet Score in a Diet Management System

Abstract

In this work we want to study the possibility to integrate a Mediterranean Diet Score into an existing diet management architecture. The main goal is to integrate the quantitative constraints on macronutrients with the qualitative constraints encoded in the Mediterranean Diet. This paper presents some preliminary results on this roadmap.

Building a Persuasive Virtual Dietitian

“…Indeed, the information on the food domain (e.g., [58]) could be used to discover and communicate connections among meals. Third, we want to augment the reasoning and generation system with the concept of the Mediterranean diet [14,59], which relies on more qualitative constraints that must be combined with the quantitative constraints on the macronutrients. Finally, we want to enrich the explanation with a suggestion on the best dishes to eat in the future meals.…”

“…Finally, in future versions of the system, we intend to investigate the possibility to account for constraints arising from allergies and similar medical situations. In a recent work [14], we proposed to exploit an ontological modelling of ingredients and recipes that can play an important role in the extension of MADiMan for allergies. For instance, if a user is allergic to legumes, the system can exclude "pasta with beans" by recovering the information that (1) "pasta with beans" contains beans and (2) beans are legumes.…”

“…We showed that the STP reasoner outperformed a greedy baseline reasoner and provided a good solution for managing a healthy diet, significantly improving the achievement of the diet goals in the case of dietary transgressions. In [13,14], we evaluated our system in a different simulation based on the Gedeone recipe book, which contains a collection of traditional Mediterranean recipes that we also use in this paper (see Section 4). In this case as well, our system outperformed a greedy baseline reasoner.…”

“…In previous work, we discussed the general architecture of the MADiMan system [10,11] and the capacity of the reasoning module with a number of simulation experiments with virtual agents based on hospital menus [12] and on Mediterranean menus [13,14]. The research questions that we explore in this paper concern the NLG module of MADiMan, which has been partially previously described in some preliminary work [15,16].…”