上海大学学报(自然科学版) ›› 2018, Vol. 24 ›› Issue (4): 583-591.doi: 10.12066/j.issn.1007-2861.1842

• 研究论文 • 上一篇    下一篇

糖尿病患个体化食谱营养优化建模与算法实现

孔维检1,2, 王永芳1(), 童子磊2, 张红广3   

  1. 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 出版日期:2018-08-31 发布日期:2018-08-31
  • 通讯作者: 王永芳 E-mail:yfw@shu.edu.cn
  • 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

KONG Weijian1,2, WANG Yongfang1(), TONG Zilei2, ZHANG Hongguang3   

  1. 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:2016-09-22 Online:2018-08-31 Published:2018-08-31
  • Contact: WANG Yongfang E-mail:yfw@shu.edu.cn

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.

关键词: 糖尿病, 营养食谱, 非劣性排序遗传算法, 多目标优化

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.

Key words: diabetes, nutritional diet, non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ), multi-objective optimization

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