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Development of a Personalized Diet Using Structural Optimization

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Society 5.0

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 437))

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Abstract

Development of a personalized human diet with due account for a variety of different factors is associated with system analysis and formalization of accumulated data and knowledge, as well as digital intelligent technologies for their processing and making optimal decisions. The methodology of optimization and formation of personalized diets based on structural-parametric modeling is presented. The proposed approach allows one to solve the following tasks: (1) to analyze the daily diet or individual meals (breakfast, lunch, afternoon snack, dinner, additional meals (snacks)) with a known quantitative set of finished products in terms of energy value and chemical composition in order to reveal dietary disorders; (2) to calculate for a specified list of finished products their optimal quantity, as close as possible in all respects to the reference diet recommended depending on mental and physical activity; (3) to optimize the diet depending on the task at hand by selecting a group of finished products from a complete or selected list of archival data, equally taking into account all the necessary parameters of each product quality; (4) to adjust the diet taking into account dietary deviations in certain parameters of chemical composition and energy value by additionally introduced products of increased biological value for special purposes, multivitamin and multivitamin-mineral supplements, as well as natural bioactive substances.

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References

  1. Lichtenstein, H., Appel, L.J., Vadiveloo, M., Hu, F.B., Kris-Etherton, P.M., Rebholz, C.M., et al.: Dietary guidance to improve cardiovascular health: a scientific statement from the American heart association. Circulation 144, e472–e477 (2021)

    Article  Google Scholar 

  2. Ayoub, J., Samra, A., Hlais, A., Bassil, M., Obeid, O.: Effect of phosphorus supplementation on weight gain and waist circumference of overweight/obese adults: a randomized clinical trial. Nutr. Diabetes 5(12), e189 (2015)

    Article  Google Scholar 

  3. Mattar, L., Zeeni, N., Bassil, M.: Effect of movie violence on mood, stress, appetite perception and food preferences in a random population. Eur. J. Clin. Nutr. 69(8), 972–973 (2015)

    Article  Google Scholar 

  4. Stigler, G.: The cost of subsistence. Am. J. Agr. Econ. 27(2), 303–314 (1945)

    Google Scholar 

  5. Lancaster, L.: The history of the application of mathematical programming to menu planning. Eur. J. Oper. Res. 57(3), 339–347 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  6. Lenstra, H.: Integer programming with a fixed number of variables. Math. Oper. Res. 8(4), 538–548 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  7. Schniederjans, M.: Goal programming: methodology and applications, 1st edn. Springer, New York (1995)

    Book  MATH  Google Scholar 

  8. McCann-Rugg, M., White, G., Endres, J.: Using goal programming to improve the calculation of diabetic diets. Comput. Oper. Res. 10(4), 365–373 (1983)

    Article  Google Scholar 

  9. Bassi, L.: The diet problem revisited. Am. Econ. 20(2), 35–39 (1976)

    Google Scholar 

  10. Foytik, J.: Devising and using a computerized diet: an exploratory study. J. Consum. Aff. 15(1), 158–169 (1981)

    Article  Google Scholar 

  11. Valdez-Pena, H., Martinez-Alfaro, H.: Menu planning using the exchange diet system. In: International Conference on Systems, Man and Cybernetics, SMC’03, vol. 3, pp. 3044–3049. IEEE (2003)

    Google Scholar 

  12. Ainsworth, B., Haskell, W., Herrmann, S., Meckes, B.D.J.N., Tudor-Locke, C., Greer, V.J.J., Whitt-Glover, M., Leon, A.: 2011 compendium of physical activities: a second update of codes and MET values. Med. Sci. Sports Exerc. 43(8), 1575–1581 (2011)

    Article  Google Scholar 

  13. Fister, D., Fister, R.S.I.: Generating eating plans for athletes using the particle swarm optimization. In: 17th International Symposium on Computational Intelligence and Informatics (CINTI’2016), pp. 193–198. IEEE (2016)

    Google Scholar 

  14. Noor, S., Mohd, A., Ruhana, K., Mahamud, K., Arbin, N.: Self-adaptive hybrid genetic algorithm (SHGA). Far East J. Math. Sci. 103, 171–190 (2018)

    Google Scholar 

  15. Seljak, B.: Computer-based dietary menu planning. J. Food Compos. Anal. 22(5), 414–420 (2009)

    Article  Google Scholar 

  16. Türkmenoglu, C., Etaner-Uyar, A.S., Kiraz, B.: Recommending healthy meal plans by optimising nature-inspired many- objective diet problem. Health Inform. J. 2127(1), 146045822097671 (2021)

    Article  Google Scholar 

  17. Salloum, G., Tekli, J.: Automated and personalized meal plan generation and relevance scoring using a multi-factor adaptation of the transportation problem. Soft. Comput. 26, 2561–2585 (2022)

    Article  Google Scholar 

  18. Bianchi, L., Dorigo, M., Gambardella, L., Gutjahr, W.: A survey on metaheuristics for stochastic combinatorial optimization. Nat. Comput. 8(2), 239–287 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  19. El-Ghazi, T.: Metaheuristics: From Design to Implementation. Wiley, New Jersey (2009)

    MATH  Google Scholar 

  20. Husain, W., Wei, L., Cheng, Z.N.S.: Application of data mining techniques in a personalized diet recommendation system for cancer patients. In: 2011 IEEE Colloquium on Humanities, Science and Engineering, pp. 239–244. IEEE (2011)

    Google Scholar 

  21. Khan, A.S., Hoffmann, A.: An advanced artificial intelligence tool for menu design. Nutr. Health 17(1), 43–53 (2003)

    Article  Google Scholar 

  22. Khan, A.S., Hoffmann, A.: Building a case-based diet recommendation system without a knowledge engineer. Artif. Intell. Med. 27(2), 155–179 (2003)

    Article  Google Scholar 

  23. Petot, G.J., Marling, C., Sterling, L.: An artificial intelligence system for computer-assisted menu planning. J. Am. Diet. Assoc. 98(9), 1009–1014 (1998)

    Article  Google Scholar 

  24. Lee, C., Wang, M., Hsu, C., Hagras, H.: A novel type-2 fuzzy ontology and its application to diet assessment. In: International Joint Conference on Web Intelligence and Intelligent Agent Technology, vol. 3, pp. 417–420. IEEE/WIC/ACM (2009)

    Google Scholar 

  25. Lee, C.S., Wang, M.H., Acampora, G., Hsu, C.Y., Hagras, H.: Diet assessment based on type-2 fuzzy ontology and fuzzy markup language. Int. J. Intell. Syst. 25(12), 1187–1216 (2010)

    Google Scholar 

  26. Wang, M.H.: Intelligent ontological multi-agent for healthy diet planning. In: International Conference on Fuzzy Systems, pp. 751–756. IEEE (2009)

    Google Scholar 

  27. Lee, C., Wang, M., Habras, H., Chen, Z., Lan, S., Hsu, C., Kuo, S., Kuo, H., Cheng, H.: A novel genetic fuzzy markup language and its application to healthy diet assessment. Int. J. Uncertainty Fuzziness Knowl.-Based Syst. 20(supp. 02), 247–278 (2012)

    Article  Google Scholar 

  28. Lee, C., Lan, S.: Adaptive personalized diet linguisticrecommendation mechanism based on type-2 fuzzy sets and genetic fuzzy markup language. IEEE Trans. Fuzzy Syst. 23(5), 1777–1802 (2015)

    Google Scholar 

  29. Evans, D.: MyFitnessPal. Br. J. Sports Med. 51(14), 1101–1102 (2017)

    Article  Google Scholar 

  30. Livestrong Foundation. MyPlateCalorie Counter. https://www.livestrong.com/myplate/. Accessed 1 May 2022

  31. MyNetDiary. https://www.mynetdiary.com/. Accessed 1 May 2022

  32. EatThisMuch Inc.: Eat this much. https://www.eatthismuch.com/. Accessed 1 May 2022

  33. Fitness Meal Planner. http://www.fitnessmealplanner.com/. Accessed 1 May 2022

  34. MakeMyPlate Inc.: Make my plate. http://www.makemyplate.co/. Accessed 1 May 2022

  35. Yang, L., Hsieh, C.K., Yang, H., Dell, N., Belongie, S., Cole, C., Estrin, D.: Yum-Me: a personalized nutrient-based meal recommender system. ACM Trans. Inf. Syst. 36(1), 1–31 (2018)

    Google Scholar 

  36. Ivashkin, Yu.A., Nikitina, M.A.: The concept of biological compatibility in optimization of a human diet. Sci. Intensive Technol. 19(3), 33–44 (2018). (In Russian)

    Google Scholar 

  37. Nikitina, M.: Structural-parametric modeling in human healthy nutrition system. In: 6th International Conference Information Technology and Nanotechnology. Session Data Science, pp. 219–224. CEUR Workshop Proceedings (2020)

    Google Scholar 

  38. Ivashkin, Yu.A.: Structural-parametric modeling and identification of anomalous situations in complex technological systems. Manag. Prob. 3, 39–43 (2003). (In Russian)

    Google Scholar 

  39. Development of ways to prevent diseases and improve health status by adjusting diets. In: Modern Technologies of Functional Food Products, pp. 422–425. DeLiplus, Moscow (2018). (In Russian)

    Google Scholar 

  40. Nikitina, M.A.: Digital technology in the development of healthy diet decision support system. In: Kravets, A., Bolshakov, A., Shcherbakov, M. (eds.) Society 5.0: Human-Centered Society Challenges and Solutions, vol. 416, pp. 65–74. Springer, Heidelberg (2022)

    Google Scholar 

  41. Nikitina, M.A.: Personalization in the structural optimization of the individual human nutrition diet. Math. Methods Technol. Technics 1, 85–88 (2022). (In Russian)

    Article  Google Scholar 

  42. Nikitina, M.A., Lisitsyn, A.B., Zakharov, A.N., Sus’, E.B., Pilyugina, S.A., Dydykin, A.S., Ustinova, A.V.: Food products. Database Registration Certificate RU 2015620557 (2015). (In Russian)

    Google Scholar 

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Acknowledgements

This chapter is prepared as part of scientific research theme No. 0585-2019-0008 under the state assignment of the federal state budgetary scientific institution ‘V. M. Gorbatov’s Federal Research Centre for Food Systems’ of RAS.

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Correspondence to Marina A. Nikitina .

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Nikitina, M.A. (2023). Development of a Personalized Diet Using Structural Optimization. In: Kravets, A.G., Bolshakov, A.A., Shcherbakov, M.V. (eds) Society 5.0. Studies in Systems, Decision and Control, vol 437. Springer, Cham. https://doi.org/10.1007/978-3-031-35875-3_4

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  • DOI: https://doi.org/10.1007/978-3-031-35875-3_4

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