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Characteristics of Heart Rate Variability Derived from ECG during the Driver's Wake and Sleep States

운전자 졸음 및 각성 상태 시 ECG신호 처리를 통한 심장박동 신호 특성

  • Kim, Min Soo (Department of Aviations Information & Communication Engineering, Kyungwoon University) ;
  • Kim, Yoon Nyun (Dongsan Medical Center, Keimyung University) ;
  • Heo, Yun Seok (Biomedical Engineering, School of Medicine, Keimyung University)
  • 김민수 (경운대학교 항공정보통신공학과) ;
  • 김윤년 (계명대학교 동산의료원) ;
  • 허윤석 (계명대학교 의과대학 의용공학과)
  • Received : 2013.10.31
  • Accepted : 2014.02.26
  • Published : 2014.04.01

Abstract

Distinct features in heart rate signals during the driver's wake and sleep states could provide an initiative for the development of a safe driving systems such as drowsiness detecting sensor in a smart wheel. We measured ECG from health subjects ($23.5{\pm}2.5$ in age) during the wake and drowsiness states. The proposed method is able to detect R waves and R-R interval calculation in the ECG even when the signal includes in abnormal signals. Heart rate variability(HRV) was investigated for the time domain and frequency domains. The STD HR(0.029), NN50(0.044) and VLF power(0.0018) of the RR interval series of the subjects were significantly different from those of the control group (p < 0.05). In conclusion, there are changes in heart rate from wake to drowsiness that are potentially to be detected. The results in our study could be useful for the development of drowsiness detection sensors for effective real-time monitoring.

Keywords

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  1. Development of a Classification Model for Driver's Drowsiness and Waking Status Using Heart Rate Variability and Respiratory Features vol.35, pp.5, 2016, https://doi.org/10.5143/JESK.2016.35.5.371