Determining the influence of visual training on EEG activity patterns using association rule mining

Fangfang Yan, Paul A. Watters, Wei Wang*

*Corresponding author for this work

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

Abstract

To confirm that visual training can change EEG patterns by association rule mining method, firstly, we collected the EEG of people who are under a long-term visual professional training (visual training group) and novice people (control group) during a specific mental tasks. Secondly, we determined the difference of brain electrical activity between the two groups using machine learning methods. Thirdly, we discovered distinct patterns using association rule algorithm, finding that the two groups were separable based on their completion of visual professional cognitive tasks. In the beta band, visual training group showed a specific and significant association pattern which included FP1 and C4. The results indicate that the EEG patterns were modified because of visual professional training. We further discuss the impact of long-term visual professional training on the EEG.

Original languageEnglish
Title of host publicationProceedings: 2011 First International Workshop on Complexity and Data Mining
Subtitle of host publicationIWCDM 2011
Place of PublicationPiscataway, USA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages64-67
Number of pages4
ISBN (Electronic)9780769546851
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 1st International Workshop on Complexity and Data Mining, IWCDM 2011 - Nanjing, Jiangsu, China
Duration: 24 Sep 201128 Sep 2011

Conference

Conference2011 1st International Workshop on Complexity and Data Mining, IWCDM 2011
CountryChina
CityNanjing, Jiangsu
Period24/09/1128/09/11

Keywords

  • Association rule mining
  • Brain development
  • EEG
  • Professional training
  • Visual training

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