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http://dx.doi.org/10.6109/jkiice.2008.12.12.2349

Pattern classification of the synchronized EEG records by an auditory stimulus for human-computer interface  

Lee, Yong-Hee (한라대학교 공과대학 컴퓨터공학과)
Choi, Chun-Ho (한라대학교 정보산업대학원)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.12, no.12, 2008 , pp. 2349-2356 More about this Journal
Abstract
In this paper, we present the method to effectively extract and classify the EEG caused by only brain activity when a normal subject is in a state of mental activity. We measure the synchronous EEG on the auditory event when a subject who is in a normal state thinks of a specific task, and then shift the baseline and reduce the effect of biological artifacts on the measured EEG. Finally we extract only the mental task signal by averaging method, and then perform the recognition of the extracted mental task signal by computing the AR coefficients. In the experiment, the auditory stimulus is used as an event and the EEG was recorded from the three channel $C_3-A_1$, $C_4-A_2$ and $P_Z-A_1$. After averaging 16 times for each channel output, we extracted the features of specific mental tasks by modeling the output as 12th order AR coefficients. We used total 36th order coefficient as an input parameter of the neural network and measured the training data 50 times per each task. With data not used for training, the rate of task recognition is 34-92 percent on the two tasks, and 38-54 percent on the four tasks.
Keywords
Auditory Stimulus; EEG; Neural Network; Interface;
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