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A Study on the Estimation of Blood Pressure Based on the Magneto-Plethysmography for Smart Healthcare

스마트 헬스케어를 위한 자계용적맥파 기반 혈압 추정에 관한 연구

  • Lee, Seong-Su (College of Science & Technology, Dept. of Biomedical Engineering, Konkuk University) ;
  • Lee, Kang-Hwi (College of Science & Technology, Dept. of Biomedical Engineering, Konkuk University) ;
  • Kim, Sang-Min (College of Science & Technology, Dept. of Biomedical Engineering, Konkuk University) ;
  • Lee, Hyeok-Jae (College of Science & Technology, Dept. of Biomedical Engineering, Konkuk University) ;
  • Lee, Byoung-Hun (College of Science & Technology, Dept. of Biomedical Engineering, Konkuk University) ;
  • Kim, Kyeoung-Seop (College of Science & Technology, Dept. of Biomedical Engineering, Konkuk University) ;
  • Lee, Jeong-Whan (College of Science & Technology, Dept. of Biomedical Engineering, Konkuk University)
  • Received : 2018.05.31
  • Accepted : 2018.06.25
  • Published : 2018.07.01

Abstract

High blood pressure causes various cardiovascular diseases and is associated with mortality. Periodic self-monitoring and recording of blood pressure is very helpful in preventing the occurrence of secondary diseases caused by hypertension. However, existing cuff-type blood pressure monitors have many limitations. As an alternative of that, a method of estimating the blood pressure by measuring the velocity change of the blood flow using the photo plethysmography is widely known. However, photo plethysmography have a low correlation with blood flow. So, we will propose an algorithm for estimating blood pressure using the relationship between velocity change of blood flow measured by magnetic field instead of photo plethysmography and electrocardiogram. For this purpose, First, we analyzed the correlation between photo plethysmography and magneto plethysmography. the correlation between MPG and PPG was r = 0.9449. Second, we compared estimated blood pressure and measured blood pressure. In the four experiment each result was r = 0.5737, r = 0.7863, r = 0.5669, and r = 0.7445.

Keywords

References

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