研究论文

糖尿病患个体化食谱营养优化建模与算法实现

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  • 1. 上海大学 通信与信息工程学院, 上海 200444
    2. 中国科学院 上海高等研究院, 上海 200135
    3. 上海科瓴医疗科技有限公司, 上海 200443

收稿日期: 2016-09-22

  网络出版日期: 2018-08-31

基金资助

国家自然科学基金资助项目(61301113);上海市自然科学基金资助项目(13ZR1416500);教育部重点实验室开放课题资助项目

Modeling and algorithm implementation of dietary nutrition optimization for diabetic patients

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  • 1. School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
    2. Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 200135, China
    3. Shanghai Carelinker Medical Technology Co., Ltd., Shanghai 200443, China

Received date: 2016-09-22

  Online published: 2018-08-31

摘要

根据糖尿病患者自身状况设计营养膳食方案是对患者进行个体化营养治疗, 实现有效控制血糖的前提. 针对糖尿病患者对个体化营养治疗的需求, 建立可适应不同性别、身高、体重、年龄以及血糖水平患者要求的膳食营养多目标优化模型, 然后使用非劣性排序遗传算法(non-dominated sorting genetic algorithm Ⅱ, NSGA-Ⅱ) 对模型进行求解. 实验 结果显示, 每餐食谱营养均衡, 食材重量搭配合理, 可满足糖尿病患者的营养摄入需要, 表明该模型与算法的有效性和可行性, 有助于提升糖尿病膳食食谱设计的精确化.

本文引用格式

孔维检, 王永芳, 童子磊, 张红广 . 糖尿病患个体化食谱营养优化建模与算法实现[J]. 上海大学学报(自然科学版), 2018 , 24(4) : 583 -591 . DOI: 10.12066/j.issn.1007-2861.1842

Abstract

A diabetic's nutritional diet program designed according to the patient's condition is a premise for effective control of blood glucose. In view of the demand of individualized nutrition therapy for diabetes patients, a multi-objective optimization model is established to meet the requirements of patients with different genders, heights, weights, ages and blood glucose levels. The model and the algorithm are validated in a specific experiment. The results show that nutrition of designed recipes is balanced, and weights of the ingredients are reasonable so that nutritional needs of the patients can be met. The model and the algorithm are effective and feasible, with improved precision of diabetes nutrition recipe design.

参考文献

[1] Franz M J . Diabetes nutrition therapy: effectiveness, macronutrients, eating patterns and weight management[J]. The American Journal of the Medical Sciences, 2016,351(4):374-379.
[2] Mayer V L, Mc Donough K, Seligman H , et al. Food insecurity, coping strategies and glucose control in low-income patients with diabetes[J]. Public Health Nutrition, 2015,19(6):1103-1111.
[3] Zhang H, Zhao W Y. Lai R D . Effect of nutrition therapy of improved food exchange serving based on glycemic load for diabetic patients in Community[J]. Hainan Medical Journal, 2012,23(1):18-20.
[4] 綦翠华 . 《营养配餐》之食品交换份法的思考[J]. 科技视界, 2014,8(15):14-15.
[5] 张蕾, 王高平 . 共同进化遗传算法在临床营养决策中的应用[J]. 计算机应用, 2007,27(S2):193-194.
[6] Cui L, Wang G P . Clustering problem based on ant colony algorithm and it's application in dietary nutrition decision supporting system[C] // IEEE International Symposium on IT in Medicine and Education. 2008: 397-400.
[7] Pei Z K, Liu Z . Nutritional diet decision using multi-objective difference evolutionary algorithm[C] // IEEE International Conference on Computational Intelligence and Natural Computing. 2009: 77-80.
[8] Wang G P, Sun Y P, Chen Y Y . Constrained multi-objective evolutionary algorithm for application decision-making in nutrition[C] // International Conference on Computer and Communication Technologies in Agriculture Engineering. 2010: 173-176.
[9] 刘宏畅 . 改进遗传算法在营养配餐系统中的应用[D]. 北京: 北京工业大学, 2015.
[10] Guan F F, Liu W, Zhang F Q , et al. Effect of diet therapy on serum trace elements in type 2 diabetes patients[J]. Chinese Journal of Clinical Nutrition, 2005,13(6):364-367.
[11] 中国营养学会. 中国居民膳食营养素参考摄入量 [M]. 北京: 科学出版社, 2014: 23-168.
[12] 杨月欣, 王光亚, 潘兴昌 . 中国食物成分表 [M]. 2版. 北京: 北京大学医学出版社, 2009: 153-430.
[13] Deb K, Pratap A, Agarwal S , et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J] IEEE Transactions on Evolutionary Computation, 2002,6(2):182-197.
[14] Kannan S, Baskar S, Mc Calley J D , et al. Application of NSGA-Ⅱ algorithm to generation expansion planning[J]. IEEE Transactions on Power Systems, 2009,24(1):454-461.
[15] Murugan P, Kannan S, Baskar S , et al. NSGA-Ⅱ algorithm for multi-objective generation expansion planning problem[J]. Electric Power Systems Research, 2009,79(4):622-628.
[16] D'souza R G L, Sekaran K C, Kandasamy A . Improved NSGA-Ⅱ based on a novel ranking scheme[J]. Journal of Computing, 2010,2(2):91-95.
[17] Yusoff Y, Ngadiman M S, Zain A M . Overview of NSGA-Ⅱ for optimizing machining process parameters[J]. Procedia Engineering, 2011,15:3978-3983.
[18] Kaushik A, Vidyarthi D P . An energy-efficient reliable grid scheduling model using NSGA-Ⅱ[J]. Engineering with Computers, 2016,32(3):355-376.
[19] 焦广宇, 蒋卓勤 . 临床营养学 [M]. 2 版. 北京: 人民卫生出版社, 2009: 200-217.
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