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논문 기본 정보

자료유형
학술대회자료
저자정보
Kenta Tomonaga (Kyushu Institute of Technology) Sou Wakamizu (Kyushu Institute of Technology) Jun Kobayashi (Kyushu Institute of Technology)
저널정보
제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2015
발행연도
2015.10
수록면
1,805 - 1,810 (6page)

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초록· 키워드

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Here we present experimental results of classification methods for brain activity in the imagination of direction. In anticipation of its adequate performance, we used a wireless portable electroencephalography (EEG) headset to collect EEG data from subjects in the experiments, during which the subjects imagined arrows indicating one of the four directions: up, down, right, and left. The classification methods estimated the direction that the subjects imagined on the basis of their brain wave signals measured by an electrode on the portable EEG headset. We implemented several classification methods, which basically followed those of a previous study that used a medical EEG device. The classification methods consisted of a band-pass filter, fast Fourier transformation, principal component analysis, and neural network. The experimental results showed that the neural network trained with the EEG data of all subjects achieved a 52.00% classification rate. When using the EEG data of each subject, the best classification rate was 55.00%. The results using the portable EEG headset were comparable with those of the previous study.

목차

Abstract
1. INTRODUCTION
2. EEG DATA ACQUISITION
3. CLASSIFICATION METHOD
4. RESULTS
5. DISCUSSION
6. CONCLUSION
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