Document Type : Original Article
Authors
1 MSc, Software, Department of Computer, School of Engineering, Isfahan Branch (Khorasgan), Islamic Azad University of Isfahan, Iran
2 Associate Professor, Artificial Intelligence, Department of Artificial Intelligence Engineering, School of Computer Engineering, University of Isfahan, Isfahan, Iran
3 Associate Professor, Nutrition and Diet Therapy, Department of Clinical Nutrition, School of Nutrition and Food Sciences, Isfahan University of Medical Sciences, Isfahan, Iran
4 Assistant Professor, Information Technology, Department of Information Technology, School of Computer Engineering, University of Isfahan, Isfahan, Iran
Abstract
Introduction: The goal of the present study was to develop an automatic and high-performance professional nutrition and diet advisor system to help the users to evaluate their nutrition conditions and get useful nutritional information. The study also aimed to provide users with a healthy meal plan based on their physical conditions such as weight, height, age, etc.Methods: This study was an applied research towards developing an intelligent diet advisor system. We focused on fuzzy logic and artificial neural networks as the means of implementation. The dataset was collected from one thousand patients’ files chosen randomly from the files of the patients referred to a diet clinic in Isfahan City, Iran, between 2011 and 2015. The collected data were entered into excel software during four months of study.Results: The designed three-layered artificial neural system with back propagation algorithm was able to diagnose the best dietary plan among the eleven proposed plans. The designed neural networks were able to work with 92% of accuracy, while the proposed fuzzy logic-based system carried out the procedure with 97% of accuracy.Conclusion: The results of this research indicated that this dietary proposal system using neural networks and the fuzzy logic was sufficient enough to be used to propose appropriate diet and meal plans to individuals. As a result, it could allow the users to receive the very efficient diet plans after entering their personal information easily, accurately, and almost free of charge.
Keywords
- Al-Dhuhli BA, Al-Gadidi BS, Al-Alawi HH, Al-Busaidi KA. Developing a nutrition and diet expert system prototype. Proceedings of the 21th IBIMA Conference on Vision 2020: Innovation, Development Sustainability, and Economic Growth; 2013 June 27-28; Vienna, Austria.
- Ashoori M, Ghasem Aghaei N, Baraani A. Implementation of a diet expert system using fuzzy logic [Report]. Isfahan, Iran: University of Isfahan; 2009. [In Persian].
- Ramachandran S, Singh H, Bajaj KK. Nutrition diet Programme-an expert system [Online]. [cited 1992]; Available from: URL:https://www.aaai.org/Papers/Symposia/Fall/1992/FS-92-01/FS92-01-023.pdf.
- Chen Y, Hsu CY, Liu L, Yang S. Constructing a nutrition diagnosis expert system. Expert Syst Appl 2012; 39(2): 2132-56.
- Krbez JM, Shaout A. Fuzzy nutrition system. International Journal of Innovative Research in Computerand Communication Engineering 2013; 1(7): 1-12.
- Heinonen P, Mannelin M, Iskala H, Juuso E. Development of a fuzzy expert system for a nutritional guidance application. Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress AND 2009 European Society of Fuzzy Logic and Technology Conference. 2009 July 20-24, Lisbon, Portugal.
- Bardella TU, de Sousa RN, Ferreira HS, Omar N, Dotto Stump SM, Silveira IF. Reviews usability of a software for diet control using artificial intelligence. Proceedings of the 12th International Conference on e-Society; 2014 Feb. 28-Mar 2; Madrid, Spain.
- Sheikh F, Group of authors Dietetic Association. Guide treatment regimen. Tehran, Iran: Marzdanesh Publications; 2006. [In Persian].
- Mahan K, Kraus MV, Scott SS. Basics of nutrition. Trans. Shidfar F, Kholdi N. Tehran, Iran: Jameia Negar Publications; 2011. [In Persian].
)