儿童癫痫综合征智能分析:综述与展望  

Intelligent Analysis of Childhood Epileptic Syndrome:Overview and Prospect

作　　者：郑润泽 冯袁盟 胡丁寒 蒋铁甲 高峰[3,4] 曹九稳 ZHENG Runze;FENG Yuanmeng;HU Dinghan;JIANG Tiejia;GAO Feng;CAO Jiuwen(School of Automation,Hangzhou Dianzi University,Hangzhou 310018;Machine Learning and I-health International Cooperation Base of Zhejiang Province,Hangzhou Dianzi University,Hangzhou 310018;Neurology Department,Children′s Hospital,School of Medi-cine,Zhejiang University,Hangzhou 310052;National Clinical Research Center for Child Health,Children′s Hospital,School of Medicine,Zhejiang University,Hangzhou 310003)

机构地区：[1]杭州电子科技大学自动化学院,杭州310018 [2]杭州电子科技大学浙江省机器学习与智慧健康国际合作基地,杭州310018 [3]浙江大学医学院附属儿童医院神经内科,杭州310052 [4]浙江大学医学院附属儿童医院国家儿童健康与疾病临床医学研究中心,杭州310003

出　　处：《模式识别与人工智能》2024年第2期144-161,共18页Pattern Recognition and Artificial Intelligence

基　　金：国家重点研发计划项目(No.2021YFE0100100,2021YFE0205400);国家自然科学基金联合项目(No.U1909209);浙江省自然科学基金重点项目(No.LZ24F030010);浙江省教育厅一般科研项目(No.Y202249784)资助。

摘　　要：儿童癫痫综合征智能分析是指通过统计分析、机器学习等数据驱动方法,挖掘临床有效生物标志物,构建相应的专家系统,以解决临床和预后管理问题的研究.文中首先简述儿童癫痫综合征的定义、发作类型和分类等临床基础知识.然后,回顾基于脑电信号的儿童癫痫综合征智能分析框架和各组成部分典型方法存在的优缺点,包括数据收集及预处理、特征提取、决策器系统和专家系统.其中,将专家系统分为特定波形检测系统、诊断分类系统、发作检测系统、发作预测系统和量化评估系统,并进行全面概括与理论解释.最后,结合儿童癫痫综合征智能分析领域现有研究的局限性和挑战,展望未来研究方向,以推动儿童癫痫综合征智能分析系统的研究进展,减轻该病带来的负面影响.The intelligent analysis of childhood epileptic syndrome refers to the research which aims at addressing clinical and prognostic management issues by data-driven methods such as statistical analysis and machine learning to explore clinically effective biomarkers and construct corresponding expert systems.Firstly,the definition,seizure types and classification of childhood epileptic syndrome are briefly introduced.Then,the advantages and disadvantages of the framework and typical methods of the intelligent analysis of childhood epileptic syndrome based on scalp electroencephalogram are reviewed,including data collection and preprocessing,feature extraction,decision-making systems,and expert systems.Specifically,the expert systems are divided into specific waveform detection systems,diagnostic classification systems,seizure detection systems,seizure prediction systems and quantitative assessment systems with a comprehensive summary and theoretical explanation.Finally,with the consideration of the limitations and challenges of the existing research in the field of intelligent analysis of childhood epileptic syndrome,future research directions are proposed to advance the study of intelligent analysis systems for childhood epileptic syndrome and alleviate the negative impact of the disease.

关 键 词：儿童癫痫综合征 生物标志物 脑电信号 智能分析 专家系统 

分 类 号：TN911.7[电子电信—通信与信息系统] TP183[电子电信—信息与通信工程] R742.1[自动化与计算机技术—控制理论与控制工程]