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KMID : 1137820090300050428
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의공학회지
2009 Volume.30 No. 5 p.428 ~ p.437
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Performance Evaluation of EEG-BCI Interface Algorithm in BCI(Brain Computer Interface)-Naive Subjects
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Kim Jin-Kwon
Kang Dae-Hoon
Lee Young-Bum
Jeong Hee-Kyo
Lee In-Su
Park Hae-Dae
Kim Eun-Ju
Lee Myoung-Ho
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Abstract
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The Performance research about EEG-BCI algorithm in BCI-naive subjects is very important for evaluating the applicability to the public. We analyzed the result of the performance evaluation experiment about the EEG-BCI algorithm in BCI-naive subjects on three different aspects. The EEG-BCI algorithm used in this paper is composed of the common spatial pattern(CSP) and the least square linear classifier. CSP is used for obtaining the characteristic of event related desynchronization, and the least square linear classifier classifies the motor imagery EEG data of the left hand or right hand. The performance evaluation experiments about EEG-BCI algorithm is conducted for 40 men and women whose age are 23.872.47. The performance evaluation about EEG-BCI algorithm in BCI-naive subjects is analyzed in terms of the accuracy, the relation between the information transfer rate and the accuracy, and the performance changes when the different types of cue were used in the training session and testing session. On the result of experiment, BCI-naive group has about 20% subjects whose accuracy exceed 0.7. And this results of the accuracy were not effected significantly by the types of cue. The Information transfer rate is in the inverse proportion to the accuracy. And the accuracy shows the severe deterioration when the motor imagery is less then 2 seconds.
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KEYWORD
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Index Terms - Brain Computer Interface, Common Spatial Pattern, EEG, Performance evaluation
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