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一类面向中风后吞咽功能障碍康复治疗的群体智慧涌现方法

宿翀 高月 李宏光 刘晓华

宿翀, 高月, 李宏光, 刘晓华. 一类面向中风后吞咽功能障碍康复治疗的群体智慧涌现方法. 自动化学报, 2017, 43(7): 1190-1201. doi: 10.16383/j.aas.2017.c160190
引用本文: 宿翀, 高月, 李宏光, 刘晓华. 一类面向中风后吞咽功能障碍康复治疗的群体智慧涌现方法. 自动化学报, 2017, 43(7): 1190-1201. doi: 10.16383/j.aas.2017.c160190
SU Chong, GAO Yue, LI Hong-Guang, LIU Xiao-Hua. A Generating Approach to Group's Intelligence with Application to Dysphagia's Rehabilitation Treatment after Stroke. ACTA AUTOMATICA SINICA, 2017, 43(7): 1190-1201. doi: 10.16383/j.aas.2017.c160190
Citation: SU Chong, GAO Yue, LI Hong-Guang, LIU Xiao-Hua. A Generating Approach to Group's Intelligence with Application to Dysphagia's Rehabilitation Treatment after Stroke. ACTA AUTOMATICA SINICA, 2017, 43(7): 1190-1201. doi: 10.16383/j.aas.2017.c160190

一类面向中风后吞咽功能障碍康复治疗的群体智慧涌现方法

doi: 10.16383/j.aas.2017.c160190
基金项目: 

国家自然科学基金 61603023

北京市优秀人才资助项目 2015000020124G041

中国科学院复杂系统管理与控制国家重点实验室开放课题 20150103

详细信息
    作者简介:

    宿翀 北京化工大学信息学院讲师.主要研究方向为人工智能, 情感计算和智能医疗.E-mail:suchong@mail.buct.edu.cn

    高月 北京化工大学信息学院硕士研究生.主要研究方向为智能决策.E-mail:18810255106@163.com

    李宏光:刘晓华 北京市积水潭医院物理康复科副主任医师.主要研究方向为康复医学诊疗.E-mail:bbjliuxhua@sina.com

    通讯作者:

    李宏光 北京化工大学信息学院教授.主要研究方向为化工过程的建模, 控制和优化.本文的通信作者.E-mail:lihg@mail.buct.edu.cn

A Generating Approach to Group's Intelligence with Application to Dysphagia's Rehabilitation Treatment after Stroke

Funds: 

Supported by National Natural Science Foundation of China 61603023

Beijing Outstanding Talent Training Project 2015000020124G041

Open Research Project from the State Key Laboratory of Management and Control for Complex Systems 20150103

More Information
    Author Bio:

     Lecturer at Beijing University of Chemical Technology. His research interest covers intelligent applications, afiect computing, and smart medicine

     Master student at Beijing University of Chemical Technology.Her main research interest is intelligent decision making

     Associate professor at Beijing Jishuitan Hospital. Her research interest covers diagnosis and treatment in rehabilitation medicine

    Corresponding author: LI Hong-Guang Professor at Beijing University of Chemical Technology. His research interest covers modeling, control and optimization of chemical process as well as computer based intelligent control for industrial plants. Corresponding author of this paper.E-mail:lihg@mail.buct.edu.cn
  • 摘要: 传统的中风后吞咽功能障碍康复治疗方案的制订通常以会诊方式,需要群体专家对所有可能的备选治疗方案进行讨论与决策,增加专家主观疲劳,且缺乏针对群体治疗智慧涌现方法的探讨,基层康复医师难以学习群体专家治疗智慧.基于多属性群决策理论,本文提出了群体智慧定义,给出了基于"专家讨论后的备选方案排序结果——子属性特征"的群体智慧涌现方法以及基于群体智慧的多属性决策方法,使计算机逐步学习群体专家经验并代替专家决策,减轻群体专家疲劳感,并具备针对未知备选方案进行自动决策的能力.针对一类数值实例,对传统多属性决策方法与所提决策方法进行了对比,并将所提方法应用于一类实际中风后吞咽功能障碍康复治疗中,验证了本文所提方法的正确性与可行性.
    1)  本文责任编委 吕金虎
  • 图  1  中风后吞咽功能障碍治疗流程图

    Fig.  1  The treatment flow chart of dysphagia after stroke

    图  2  群体智慧涌现算法流程图

    Fig.  2  The flow chart of group intelligence algorithms

    图  3  子属性权重进化曲线

    Fig.  3  The evolutions of the sub-attribute's weight

    图  4  子属性可达区间下限的进化曲线

    Fig.  4  The evolutions of the sub-attribute's lower limit

    图  5  子属性可达区间上限的进化曲线

    Fig.  5  The evolutions of the sub-attribute's upper limit

    图  6  子属性权重进化曲线

    Fig.  6  The evolutions of the sub-attribute's weight

    图  7  子属性可达区间下限的进化曲线

    Fig.  7  The evolutions of the sub-attribute's lower limit

    图  8  子属性可达区间上限的进化曲线

    Fig.  8  The evolutions of the sub-attribute's upper limit

    图  9  基于所提决策方法与专家会诊的物理治疗时间对比图

    Fig.  9  The physical therapy time comparison chart based on the proposed decision method and expert consultation

    图  10  基于所提决策方法与专家会诊的按摩时间对比图

    Fig.  10  The massage time comparison chart based on the proposed decision method and expert consultation

    图  11  基于所提决策方法与专家会诊的针灸时间对比图

    Fig.  11  The acupuncture time comparison chart based on the proposed decision method and expert consultation

    表  1  备选方案集

    Table  1  The alternatives

    u1u2u3
    x12.33.40.9
    x24.98.01.4
    x33.25.61.3
    x45.06.81.9
    x51.42.01.8
    下载: 导出CSV

    表  2  规范阵

    Table  2  The standard matrix

    u1u2u3
    S10.460.420.47
    S20.9810.74
    S30.640.70.68
    S410.851
    S50.280.250.95
    下载: 导出CSV

    表  3  备选方案集

    Table  3  The alternatives

    u1u2u3
    x1111217
    x214919
    x316518
    x412720
    下载: 导出CSV

    表  4  方案准确率对照表

    Table  4  The accuracy comparison of the treatment plan

    编号准确系数
    物理治疗按摩针灸平均
    11.000.850.940.93
    20.920.900.930.92
    30.901.001.000.97
    40.870.901.000.92
    50.901.000.930.94
    60.931.001.000.98
    70.80.950.920.89
    810.940.920.95
    90.90.9510.95
    1010.90.90.93
    下载: 导出CSV
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  • 收稿日期:  2016-03-03
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