Analysis of attention deficit hyperactivity disorder in EEG using wavelet transform and self organizing maps

Seung Hyun Lee, Berdakh Abibullaev, Won Seok Kang, Yunhee Shin, Jinung An

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper presents our preliminary study EEG brain signals of children with attention deficit hyperactivity disorder (ADHD) in order to support a computer assisted diagnostic system. The EEG signals were recorded from 13 children including normal and children diagnosed with ADHD. We analyzed the signals with multilevel discrete wavelet decompositions in order to extract brain signal power spectrum features. A wavelet thresholding technique was employed to further improve the data quality by denoising the artifacts. In order to discriminate the attention level in electrical brain activity of ADHD children, we used a standard Self-Organizing Map clustering technique with wavelet coefficient input features. Clustering results varied depending on the wavelet feature extraction stage, particularly it was noticed that accuracy was dependent on the type of the used wavelet function. The clustering results demonstrate that 'sym7' wavelet function provides better input feature localization to provide the accurate separation of normal and disordered children's brain activity.

Original languageEnglish
Title of host publicationICCAS 2010 - International Conference on Control, Automation and Systems
Pages2439-2442
Number of pages4
Publication statusPublished - 2010
Externally publishedYes
EventInternational Conference on Control, Automation and Systems, ICCAS 2010 - Gyeonggi-do, Korea, Republic of
Duration: Oct 27 2010Oct 30 2010

Other

OtherInternational Conference on Control, Automation and Systems, ICCAS 2010
CountryKorea, Republic of
CityGyeonggi-do
Period10/27/1010/30/10

Fingerprint

Self organizing maps
Electroencephalography
Wavelet transforms
Brain
Wavelet decomposition
Power spectrum
Feature extraction

Keywords

  • ADHD
  • EEG
  • SOM
  • Wavelet

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

Cite this

Lee, S. H., Abibullaev, B., Kang, W. S., Shin, Y., & An, J. (2010). Analysis of attention deficit hyperactivity disorder in EEG using wavelet transform and self organizing maps. In ICCAS 2010 - International Conference on Control, Automation and Systems (pp. 2439-2442). [5670255]

Analysis of attention deficit hyperactivity disorder in EEG using wavelet transform and self organizing maps. / Lee, Seung Hyun; Abibullaev, Berdakh; Kang, Won Seok; Shin, Yunhee; An, Jinung.

ICCAS 2010 - International Conference on Control, Automation and Systems. 2010. p. 2439-2442 5670255.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lee, SH, Abibullaev, B, Kang, WS, Shin, Y & An, J 2010, Analysis of attention deficit hyperactivity disorder in EEG using wavelet transform and self organizing maps. in ICCAS 2010 - International Conference on Control, Automation and Systems., 5670255, pp. 2439-2442, International Conference on Control, Automation and Systems, ICCAS 2010, Gyeonggi-do, Korea, Republic of, 10/27/10.
Lee SH, Abibullaev B, Kang WS, Shin Y, An J. Analysis of attention deficit hyperactivity disorder in EEG using wavelet transform and self organizing maps. In ICCAS 2010 - International Conference on Control, Automation and Systems. 2010. p. 2439-2442. 5670255
Lee, Seung Hyun ; Abibullaev, Berdakh ; Kang, Won Seok ; Shin, Yunhee ; An, Jinung. / Analysis of attention deficit hyperactivity disorder in EEG using wavelet transform and self organizing maps. ICCAS 2010 - International Conference on Control, Automation and Systems. 2010. pp. 2439-2442
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