- Title
- Determining the influence of visual training on EEG activity patterns using association rule mining
- Creator
- Yan, Fangang; Watters, Paul; Wang, Wei
- Date
- 2011
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/40143
- Identifier
- vital:4594
- Identifier
-
https://doi.org/10.1109/IWCDM.2011.23
- 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. © 2011 IEEE.
- Publisher
- Nanjing, Jiangsu IEEE
- Rights
- IEEE
- Rights
- This metadata is freely available under a CCO license
- Subject
- Association rule mining; Brain development; EEG; Professional training; Visual training; Association patterns; Association rule algorithm; Association rule mining methods; Brain electrical activity; Cognitive task; Control groups; EEG activity; EEG pattern; Machine learning methods; Mental tasks; Association rules; Brain; Data mining; Learning systems; Personnel training; Professional aspects; Electroencephalography
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