Optimal EEG Data Segmentation in LSTM Networks for Learning Neural Dynamics of ADHD

I. Wen Huang, Yang Chang, Cory Stevenson, I. Chun Chen, Dar Shong Lin, Li Wei Ko

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Attention deficit/hyperactivity disorder (ADHD) is a condition that generally affects the neurodevelopment of children. Both electroencephalography (EEG) and continuous performance tests (CPT) can be used not only to provide objective identification ADHD, but also to directly observe and quantify the performance of subject task performance. In this study, we propose an optimized segmentation for learning EEG time-series information with long short-term memory (LSTM) networks used to differentiate ADHD and neurotypical (NT) children. A total of 30 NT children and 30 children diagnosed with ADHD participated in CPT while simultaneously monitored with EEG. The experimental results show that, whether it is a single feature of beta power at a the O2 electrode location or all the features, the optimal data segment is the same, an EEG segment containing the data from 30 seconds of eyes-open resting and 30 seconds of CPT task. This produced improved performance for discriminating the differences in EEG between the two groups, thus assisting in the diagnosis of ADHD.

Original languageEnglish
Title of host publicationICSSE 2022 - 2022 International Conference on System Science and Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages33-38
Number of pages6
ISBN (Electronic)9781665488525
DOIs
StatePublished - 2022
Event2022 International Conference on System Science and Engineering, ICSSE 2022 - Virtual, Online, Taiwan
Duration: 26 May 202229 May 2022

Publication series

NameICSSE 2022 - 2022 International Conference on System Science and Engineering

Conference

Conference2022 International Conference on System Science and Engineering, ICSSE 2022
Country/TerritoryTaiwan
CityVirtual, Online
Period26/05/2229/05/22

Keywords

  • ADHD
  • EEG
  • continuous performance test
  • long short-term memory network
  • optimization

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