Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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Automatic Detection of Slow-Wave Sleep Based on Electrocardiogram

심전도를 이용한 서파 수면 자동 검출 알고리즘 개발

  • Yoon, Hee Nam (Interdisciplinary Program in Bioengineering, Seoul National University) ;
  • Hwang, Su Hwan (Interdisciplinary Program in Bioengineering, Seoul National University) ;
  • Jung, Da Woon (Interdisciplinary Program in Bioengineering, Seoul National University) ;
  • Lee, Yu Jin (Department of Neuropsychiatry and the Center for Sleep and Chronobiology, Seoul National University Hospital) ;
  • Jeong, Do-Un (Department of Neuropsychiatry and the Center for Sleep and Chronobiology, Seoul National University Hospital) ;
  • Park, Kwang Suk (Department of Biomedical Engineering, Seoul National University College of Medicine)
  • 윤희남 (서울대학교 공과대학 협동과정 바이오엔지니어링 전공) ;
  • 황수환 (서울대학교 공과대학 협동과정 바이오엔지니어링 전공) ;
  • 정다운 (서울대학교 공과대학 협동과정 바이오엔지니어링 전공) ;
  • 이유진 (서울대학교병원 수면의학센터) ;
  • 정도언 (서울대학교병원 수면의학센터) ;
  • 박광석 (서울대학교 의과대학 의공학교실)
  • Received : 2014.10.06
  • Accepted : 2014.11.17
  • Published : 2014.12.30
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Abstract

The objective of this research is to develop an automatic algorithm based on electrocardiogram (ECG) to estimate slow-wave sleep (SWS). An algorithm is based on 7 indices extracted from heart rate on ECG which simultaneously recorded with standard full night polysomnography from 31 subjects. Those 7 indices were then applied to independent component analysis to extract a feature that discriminates SWS and other sleep stages. Overall Cohen's kappa, accuracy, sensitivity and specificity of the algorithm to detect 30s epochs of SWS were 0.52, 0.87, 0.70 and 0.90, respectively. The automatic SWS detection algorithm could be useful combining with existing REM and wake estimation technique on unattended home-based sleep monitoring.

Keywords

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