Summary
2011 International Symposium on Nonlinear Theory and Its Applications
2011
Session Number:A4L-E
Session:
Number:A4L-E1
Variability in EEG with Single Point Sensing as Inter-Individual Difference Measure Using Self-Organizing Map
Shin-ichi Ito, Masashi Hamaguchi, Katsuya Sato, Shoichiro Fujisawa,
pp.290-293
Publication Date:2011/9/4
Online ISSN:2188-5079
Summary:
In this paper, we introduce an EEG analysis technique to confirm an inter-individual di?erence in prefrontal cortex EEG with a single point sensing. The device for recording the EEG uses the dry-type sensor and a few numbers of electrodes. The EEG analysis adapts the feature mining on EEG pattern using a self-organizing map (SOM). The EEG patterns are determined based on the preference evaluation on sound listened to. In the preprocessing, we extract the EEG feature vector by calculating the time average on each frequency band which areθ, low-α, high-α, low-β, high-β, respectively. To confirm the inter-individual difference, we do experiments using real EEG data. These results show that the learning results by SOM on each human are clearly different when using same initial weight values for the SOM.