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基于小波相干性算法的孤独症儿童脑电评估

张丹 张帅 李小俚 康健楠

张丹, 张帅, 李小俚, 康健楠. 基于小波相干性算法的孤独症儿童脑电评估. 自动化学报, 2021, 47(3): 678-684 doi: 10.16383/j.aas.c180464
引用本文: 张丹, 张帅, 李小俚, 康健楠. 基于小波相干性算法的孤独症儿童脑电评估. 自动化学报, 2021, 47(3): 678-684 doi: 10.16383/j.aas.c180464
Zhang Dan, Zhang Shuai, Li Xiao-Li, Kang Jian-Nan. EEG assessment of autistic children based on wavelet coherence. Acta Automatica Sinica, 2021, 47(3): 678-684 doi: 10.16383/j.aas.c180464
Citation: Zhang Dan, Zhang Shuai, Li Xiao-Li, Kang Jian-Nan. EEG assessment of autistic children based on wavelet coherence. Acta Automatica Sinica, 2021, 47(3): 678-684 doi: 10.16383/j.aas.c180464

基于小波相干性算法的孤独症儿童脑电评估

doi: 10.16383/j.aas.c180464
基金项目: 

国家自然科学基金 61761166003

详细信息
    作者简介:

    张丹  燕山大学硕士研究生. 2013年获得河北大学质量技术监督学院学士学位. 主要研究方向为孤独症儿童脑电分析. E-mail: zhangdanaddress@163.com

    张帅  北京科技大学硕士研究生. 2016年获得燕山大学电气学院学士学位. 主要研究方向为硬件电路设计. E-mail: 18811457864@163.com

    李小俚  北京师范大学认知神经科学与学习国家重点实验室副主任, 北京师范大学脑调控与认知增强研究中心主任. 主要研究方向为神经信息与工程, 自动智能状态监控, 微弱信号检测与信号处理. E-mail: xiaoli@bnu.edu.cn

    通讯作者:

    康健楠  河北大学讲师. 2002年于燕山大学获得学士学位, 2006年于燕山大学获得硕士学位. 主要研究方向为孤独症儿童脑电信息处理. 本文通信作者. E-mail: kangjiannan81@163.com

  • 本文责任编委  张道强

EEG Assessment of Autistic Children Based on Wavelet Coherence

Funds: 

National Natural Science Foundation of China 61761166003

More Information
    Author Bio:

    ZHANG Dan  Master student at Yanshan University. She received her bachelor degree in 2013 from the Quality and Technical Supervision College, Hebei University. Her research interest is EEG analysis for autism children

    ZHANG Shuai  Master student at Beijing University of Science and Technology. He received his bachelor degree in 2016 from the Institute of Electrical Engineering, Yanshan University. His main research interest is hardware circuit design

    LI Xiao-Li  Deputy director of the State Key Laboratory of Cognitive Neuroscience and Learning, director of the Brain Control and Cognitive Enhancement Research Center, Beijing Normal University. His research interest covers neuroinformatics and engineering, automatic intelligent state monitoring, weak signal detection, and signal processing

    Corresponding author: KANG Jian-Nan  Lecturer at Hebei University. She received her bachelor degree in 2002 and master degree in 2006 from Yanshan University, respectively. Her main research interest is EEG information processing for autism children. Corresponding author of this paper
  • Recommended by Associate Editor ZHANG Dao-Qiang
  • 摘要: 孤独症是一种先天的大脑发育障碍性疾病, 孤独症儿童的早期评估诊断尤为重要. 脑电图(Electroencephalography, EEG)是大脑神经细胞电生理活动在大脑皮层或头皮表面的总体反映. EEG信号中包含了大量的生理与疾病信息, 可为某些脑疾病提供诊断依据. 本文按照国际10-20系统标准电极分布将全脑划分为5个脑区, 采用小波相干性算法对孤独症(Autistic spectrum disorder, ASD)儿童和正常(Typical development, TD)儿童任意两通道之间在不同节律下的连接性进行计算, 按脑区进行划分, 得到脑区内和跨脑区功能连接结果, 随后应用独立样本t检验分析和FDR (False discovery rate)多重校正方法后给出脑区内和跨脑区在不同节律下的组间差异.结果表明, ASD组相对于TD组跨脑区连接和脑区内连接普遍较弱, 除delta频段外其他频段均差异显著, 尤其是额叶与其他脑区连接. 多重校正后通道间长程连接中额叶与枕叶、中央区与枕叶在四个频段差异显著较明显, 通道间短程连接额叶在theta和alpha频段较显著, 其他频段其他脑区对比不显著.
    Recommended by Associate Editor ZHANG Dao-Qiang
    1)  本文责任编委  张道强
  • 图  1  正常儿童与孤独症儿童小波相干值对比图

    Fig.  1  Comparison of wavelet coherence values between normal children and autistic children

    图  2  正常儿童与孤独症儿童脑区小波相干值统计检验结果图

    Fig.  2  Statistical test results of wavelet coherence values between normal children and autistic children

    图  3  孤独症组与正常组脑区内通道间小波相干值显著性比较图

    Fig.  3  Statistical test results of wavelet coherence values between normal children and autistic children

    图  4  孤独症组与正常组跨脑区通道间小波相干值显著性比较图

    Fig.  4  Statistical test results of wavelet coherence values between normal children and autistic children

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  • 收稿日期:  2018-07-16
  • 录用日期:  2019-03-08
  • 刊出日期:  2021-04-02

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