Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Study of Analysis of Brain-Computer Interface System Performance using Independent Component Algorithm

독립성분분석 방법을 이용한 뇌-컴퓨터 접속 시스템 신호 분석

  • 송정화 (한림대학교 정보통신공학부) ;
  • 이현주 (한림대학교 의과대학) ;
  • 조병옥 (한림대학교 정보통신공학부) ;
  • 박수영 (한림대학교 정보통신공학부) ;
  • 신형철 (한림대학교 의과대학) ;
  • 이은주 (한림대학교 정보통신공학부) ;
  • 송성호 (한림대학교 정보통신공학부)
  • Published : 2007.09.01
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Abstract

A brain-computer interface(BCI) system is a communication channel which transforms a subject's thought process into command signals to control various devices. These systems use electroencephalographic signals or the neuronal activity of many single neurons. The presented study deals with an efficient analysis method of neuronal signals from a BCI System using an independent component analysis(ICA) algorithm. The BCI system was implemented to generate event signals coding movement information of the subject. To apply the ICA algorithm, we obtained the perievent histograms of neuronal signals recorded from prefrontal cortex(PFC) region during target-to-goal(TG) task trials in the BCI system. The neuronal signals were then smoothed over 5ms intervals by low-pass filtering. The matrix of smoothed signals was then rearranged such that each signal was represented as a column and each bin as a row. Each column was also normalized to have a unit variance. As a result, we verified that different patterns of the neuronal signals are dependent on the target position and predefined event signals.

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References

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