期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2020
卷号：11
期号：12
页码：269-276
DOI：10.14569/IJACSA.2020.0111234
出版社：Science and Information Society (SAI)
摘要：Individualized meal planning is a nutrition counseling strategy that focuses on improving food behavior changes. In the sports setting, the number of experts who are sports dietitians or nutritionists (SD/SN) is small in number, and yet the demand for creating meal planning for a vast number of athletes often cannot be met. Although some food recommender system had been proposed to provide healthy menu planning for the general population, no similar solution focused on the athlete's needs. In this study, the iDietScoreTM architecture was proposed to give athletes and active individuals virtual individualized meal planning based on their profile, includes energy and macronutrients requirement, sports category, age group, training cycles, training time and individual food preferences. Knowledge acquisition on the expert domain (the SN) was conducted prior to the system design through a semi-structured interview to understand meal planning activities' workflow. The architecture comprises: (1) iDietScoreTM web for SN/SD, (2) mobile application for athletes and active individuals and (3) expert system. SN/SD used the iDietScoreTM web to develop a meal plan and initiate the compilation meal plan database for further use in the expert system. The user used iDietScoreTM mobile app to receive the virtual individualized meal plan. An inference-based expert system was applied in the current study to generate the meal plan recommendation and meal reconstruction for the user. Further research is necessary to evaluate the prototype's usability by the target user (athletes and active individuals).
关键词：Expert system; meal planning; sports nutrition; inference engine; design and development
