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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 2
347-350

Study of EEG signal classification based on deep learning for ADHD children and normal children

Tian Bofan1,2
Yan Hanying1,2
Wang Suhong3
Zou Ling1,2
1. School of Information Science & Engineering, Changzhou University, Changzhou Jiangsu 213164, China
2. Changzhou Key Laboratory of Biomedical Information Technology, Changzhou Jiangsu 213164, China
3. Brain Science Research Center, The Third Affiliated Hospital of Soochow University, Changzhou Jiangsu 213003, China
DOI: 10.19734/j.issn.1001-3695.2017.08.0870

Abstract

To solve the classification problem of attention deficit hyperactivity disorder(ADHD) children and normal children, it the experiment studied the event-related potential of them with the classical interference control task experimental paradigm in order to distinguish two categories of children through the ERP characteristics. In the experiment, firstly it used the long short-term memory(LSTM) method to analyze the EEG signals of two kinds of children's the optimal electrodes(p<0.05) in the frontal and parietal-occipital regions during the latency(200~450 ms), learn its characteristics automatically and realize classification. The classification rate was slightly higher than the conventional method, up to 95.78%. The results show that the LSTM method is helpful to classify the EEG signals of children with ADHD, which provides a new idea for the individual diagnosis of ADHD children.

Foundation Support

江苏省科技厅社发发展项目(BE2018638)
常州市科技项目(CE20175043)
江苏省“333工程”人才项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.08.0870
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 2
Section: Algorithm Research & Explore
Pages: 347-350
Serial Number: 1001-3695(2019)02-007-0347-04

Publish History

[2019-02-05] Printed Article

Cite This Article

田博帆, 严瀚莹, 王苏弘, 等. 基于深度学习的ADHD儿童和正常儿童脑电信号分类研究 [J]. 计算机应用研究, 2019, 36 (2): 347-350. (Tian Bofan, Yan Hanying, Wang Suhong, et al. Study of EEG signal classification based on deep learning for ADHD children and normal children [J]. Application Research of Computers, 2019, 36 (2): 347-350. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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