Healthy diet assessment mechanism based on fuzzy markup language for Japanese food

Owing to the change of our lifestyle, more people suffer from chronic diseases, such as obesity or diabetes. Making improvements in terms of diet and physical activity is helpful for people to reduce the risk of suffering from these chronic diseases. This paper presents a healthy diet assessment mechanism based on fuzzy markup language (FML) for Japanese food. This mechanism is based on the dietary standard, food exchange list (FEL), published by the Japan Diabetes Society, to assess one person’s dietary healthy level according to his/her personal profile, his/her daily physical activity, and how balanced he/she consumes food items. We use FML to describe the knowledge base and the rule base of the constructed fuzzy logic system. Additionally, ontology stores the necessary knowledge base and rule base of the adopted fuzzy inference mechanism. The proposed mechanism operates as follows: (i) Dieticians first define the nutrient facts of the collected food items. (ii) The involved subjects record their personal information, eaten food items, and daily physical activity. Through the constructed FML-based personal profile ontology, the estimated energy requirement and the estimated unit requirement for each food group are obtained after inference. (iii) Finally, one-day dietary healthy level is inferred by the proposed fuzzy inference mechanism. From the experimental results, the proposed mechanism is feasible to apply to Japanese dietary assessment. In the future, we will integrate with genetic learning algorithm and collect more subjects’ records to further improve the performance.