Proceedings of the KOSOMBE Conference (대한의용생체공학회:학술대회논문집)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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Automatic Detection of Rapid Eye Movement Distribution in Narcoleptic and Normal Sleep Using Fuzzy Logic

퍼지 추론을 이용한 REM의 자동 검출 : 기면증과 정상수면의 REM 분포 연구

  • Park, H.J. (Interdisciplinary Program of Medical and Biological Engineering Major, Seoul Nat'l Univ.) ;
  • Han, J.M. (Interdisciplinary Program of Medical and Biological Engineering Major, Seoul Nat'l Univ.) ;
  • Choi, M.H. (Interdisciplinary Program of Medical and Biological Engineering Major, Seoul Nat'l Univ.) ;
  • Jeong, D.U. (Dept. of Psychiatric Science, College of Medicine, Seoul Nat'l. Univ.) ;
  • Park, K.S. (Dept. of Biomedical Engineering, College of Medicine, Seoul Nat'l. Univ.)
  • 박해정 (서울대학교 대학원 협동과정 의용생체공학, 서울대학교 의공학 연구소) ;
  • 한주만 (서울대학교 대학원 협동과정 의용생체공학, 서울대학교 의공학 연구소) ;
  • 최미혜 (서울대학교 대학원 협동과정 의용생체공학, 서울대학교 의공학 연구소) ;
  • 정도언 (서울대학교 의과대학 정신과학교실) ;
  • 박광석 (서울대학교 의과대학 의공학교실)
  • Published : 1998.11.20
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Abstract

In this paper we suggested an automated method for detecting and counting rapid eye movement(REM) using EOG during sleep. This method is formulated by two step fuzzy logic. At first step, the velocity and the distance of single channel eye movement are used for the fuzzy input to get the possibility of being REM at each EOG. At second step, the two possibility values of both EOG from the first step and the correlation coefficient of both eye movements are used for the fuzzy logic input, and the output is the final possibility of being Rapid Eye Movement. We applied this algorithm to the normal and narcoleptic sleep data and compared the difference. We found the possibility that the count of REM can be a parameter that has significant physiological meanings.

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