iDietScoreTM: Meal recommender system for athletes and active individuals

Mustafa, Norashikin and Abdul Hadi, Abd Rahman and Sani, Nor Samsiah and Mohamad, Mohd Izham and Zakaria, Ahmad Zawawi and Ahmad, Azimah and Yatiman, Noor Hafizah and Abd Talib, Ruzita and Bee Koon, Poh and Safii, Nik Shanita (2020) iDietScoreTM: Meal recommender system for athletes and active individuals. International Journal of Advanced Computer Science and Applications, 11 (12). pp. 269-276. ISSN 2158-107X E-ISSN 2156-5570

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Abstract

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 semistructured 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.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Expert system; meal planning; sports nutrition; inference engine; design and development
Subjects:	T Technology > T Technology (General) > T61 Technical education. Technical schools
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Allied Health Sciences Kulliyyah of Allied Health Sciences > Department of Nutrition Sciences
Depositing User:	Dr Norashikin Mustafa
Date Deposited:	29 Dec 2022 17:35
Last Modified:	29 Dec 2022 17:35
URI:	http://irep.iium.edu.my/id/eprint/102318

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