儿童癫痫综合征智能分析:综述与展望

doi:10.16451/j.cnki.issn1003-6059.202402004

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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.

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	郑润泽
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	曹九稳

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

Abstract：

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.

Key words： Childhood Epileptic Syndrome Biomarker Electroencephalogram Intelligent Analysis Expert System

收稿日期: 2023-11-01

ZTFLH:	TN911.7
	TP183
	R742.1

基金资助:

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

通讯作者: 曹九稳,博士,教授,主要研究方向为深度学习、神经网络、医学信号处理.E-mail:jwcao@hdu.edu.cn.

作者简介: 郑润泽,博士研究生,主要研究方向为智能信号分析与处理.E-mail:runzewuyu@hdu.edu.cn. 冯袁盟,博士研究生,主要研究方向为智能信号分析与处理.E-mail:jsnt_fym@126.com. 胡丁寒,博士,讲师,主要研究方向为机器学习、脑电信号分析与处理.E-mail:hdh@hdu.edu.cn. 蒋铁甲,硕士,副主任医师,主要研究方向为儿童神经系统疾病的电生理信号量化分析.E-mail:jiangyouze@zju.edu.cn. 高峰,硕士,教授,主要研究方向为癫痫的电生理特点和病因学.E-mail:epilepsy@zju.edu.cn.

引用本文:

郑润泽, 冯袁盟, 胡丁寒, 蒋铁甲, 高峰, 曹九稳. 儿童癫痫综合征智能分析:综述与展望[J]. 模式识别与人工智能, 2024, 37(2): 144-161. ZHENG Runze, FENG Yuanmeng, HU Dinghan, JIANG Tiejia, GAO Feng, CAO Jiuwen. Intelligent Analysis of Childhood Epileptic Syndrome: Overview and Prospect. Pattern Recognition and Artificial Intelligence, 2024, 37(2): 144-161.

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