Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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A Study on EEG based Concentration transmission and Brain Computer Interface Application

뇌파기반 집중도 전송 및 BCI 적용에 관한 연구

  • Lee, Chung-Heon (Dept. of Mechatronics Engineering, University of Tongmyung) ;
  • Kwon, Jang-Woo (Dept. of Computer Engineering, University of Tongmyung) ;
  • Kim, Gyu-Dong (Dept. of Computer Engineering, University of Tongmyung) ;
  • Lee, Jun-Oh (Dept. of Biomedical Engineering, University of Tongmyung) ;
  • Hong, Jun-Eui (Dept. of Computer Engineering, University of Tongmyung) ;
  • Lee, Dong-Hoon (Dept. of Biomedical Engineering, University of Tongmyung)
  • Published : 2008.10.31
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Abstract

This research measures EEG signals which are generating on head skin and extracts brain concentration level related with brain activity. We develop concentration wireless transmission system for controlling hardware by using this signal. Two channels are used for measuring EEG signal on front head and Biopac system with MP-100 and EEG100C was used for measuring EEG signal, amplifying and filtering the signal. LabView 8.5 was also used for FFT transformation, frequency and spectrum analysis of the measure EEG signal. As a result, ${\alpha}$ wave, ${\beta}$ wave, ${\theta}$ wave and ${\delta}$ wave were classified. we extracted the concentration index by adapting concentration extraction algorithm. This concentration index was transferred into lego automobile device by wireless module and applied for BCI application.

본 연구는 두피에서 발생하는 EEG(electroencephalog ram)신호를 측정한 후 두뇌활동과 관련된 지표 중 집중도를 추출하여 집중도의 크기에 따라 하드웨어를 제어하는 집중도 무선전송 시스템을 구연하고자 하였다. 뇌파신호를 측정하여 집중도를 추출하기 위해 두피의 좌, 우 두 채널을 사용하였으며 Biopac의 MP-100과 EEG100C을 이용하여 뇌파신호 계측, 증폭 및 필터링을 하였다. 계측된 EEG 신호로부터 특정 주파수 대역 및 스펙트럼을 분석하기 위해서 LabVIEW 8.5를 이용하여 FFT(Fast Fourier Transformation) 처리를 하였다. 이를 통해 ${\alpha}$파, ${\beta}$파, ${\theta}$파, ${\delta}$파 주파수영역으로 분류한 후 집중도 추출 알고리즘을 적용하여 집중도 지표를 추출하였고 추출된 집중도 신호를 무선전송하여 BCI(Brain Computer Interface) 기술에 응용하고자 레고 자동차에 적응하여 보았다.

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