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Light Modulation based on PPG Signal Processing for Biomedical Signal Monitoring Device

생체 정보 감시 장치를 위한 광변조 기법의 PPG 신호처리

  • Lee, Han-Wook (Department of Electronic Engineering, Gyeongsang national University) ;
  • Lee, Ju-Won (Department of Medical Engineering, Andong Science College) ;
  • Jeong, Won-Geun (Department of Robot & Aviation Electronic, Namhae college) ;
  • Kim, Seong-Hoo (Department of Electronic Engineering, Gyeongsang national University) ;
  • Lee, Gun-Ki (Department of Electronic Engineering, Gyeongsang national University)
  • 이한욱 (경상대학교 전자공학과) ;
  • 이주원 (안동과학대학 의료공학과) ;
  • 정원근 (남해대학 로봇항공전자과) ;
  • 김성후 (경상대학교 전자공학과) ;
  • 이건기 (경상대학교 전자공학과)
  • Published : 2009.12.31

Abstract

The development of technology has led to ubiquitous health care service, which enables many patients to receive medical services anytime and anywhere. For the ubiquitous health care environment, real-time measurement of biomedical signals is very important, and the medical instruments must be small and portable or wearable. So, such devices have been developed to measure biomedical signals. In this study, we develop the biomedical monitoring device which is sensing the PPG signal, one of the useful signal in the field of ubiquitous healthcare. We design a watch-like biomedical signal monitoring system without a finger probe to prevent the user's inconvenience. This system obtains the PPG from the radial artery using a sensor in the wrist band. But, new device developed in this paper is easy to get the motion artifacts. So, we proposed new algorithm removing the motion artifacts from the PPG signal. The method detects motion artifacts by changing the degree of brightness of the light source. If the brightness of the light source is reduced, the PPG pulses will disappear. When the PPG pulses have disappeared completely, the remaining signal is not the signal that results from the changing blood flow. We believe that this signal is the motion artifact and call it the noise reference signal. The motion artifacts are removed by subtracting the noise reference signal from the input signal. We apply this algorithm to the system, so we can stabilize the biomedical monitoring system we designed.

Keywords

References

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