Classification By Eeg Frequency Distribution In Imagination Of Directions
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS 18TH ANNUAL CONFERENCE, KES-2014(2014)
摘要
This paper describes the method for classification of brain state by the measured electroencephalogram (EEG) frequency in directions (up, down, left, and right) imagination. Recently, Brain-Machine Interface (BMI) has been studied in a variety of ways due to the development of brain measurement technology. Therefore, we have used the BMI to identify the human selection of directions. Our method consists of data normalization, principal component analysis and neural network. The maximum value of the identification rate was 46% by using 3 electrodes (F4, F8 and T8) in the previous study. In this study, we improved the learning method of neural network for the improvement of identification rate of brain state. For that purpose, the measurement points of EEG and the number of subjects are increased. As a result, the maximum value of the identification rate was improved. (C) 2014 Published by Elsevier B.V.
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关键词
brain-machine interface,electroencephalogram,frequency,imaging directions,principal component analysis,neural network
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