Oscillometric Blood Pressure Estimation Based on Maximum Amplitude Algorithm Employing Gaussian Mixture Regression

  • Lee, Soojeong
  • Chang, Joon-Hyuk
  • Nam, Sang Won
  • Lim, Chungsoo
  • Rajan, Sreeraman
  • 외 2명
Citations

WEB OF SCIENCE

42
Citations

SCOPUS

47

초록

This paper introduces a novel approach to estimate the systolic and diastolic blood pressure ratios (SBPR and DBPR) based on the maximum amplitude algorithm (MAA) using a Gaussian mixture regression (GMR). The relevant features, which clearly discriminate the SBPR and DBPR according to the targeted groups, are selected in a feature vector. The selected feature vector is then represented by the Gaussian mixture model. The SBPR and DBPR are subsequently obtained with the help of the GMR and then mapped back to SBP and DBP values that are more accurate than those obtained with the conventional MAA method.

키워드

Gaussian mixture regression (GMR)maximum amplitude algorithm (MAA)oscillometric blood pressure estimation
제목
Oscillometric Blood Pressure Estimation Based on Maximum Amplitude Algorithm Employing Gaussian Mixture Regression
저자
Lee, SoojeongChang, Joon-HyukNam, Sang WonLim, ChungsooRajan, SreeramanDajani, Hilmi R.Groza, Voicu Z.
DOI
10.1109/TIM.2013.2273612
발행일
2013-12
유형
Article
저널명
IEEE Transactions on Instrumentation and Measurement
62
12
페이지
3387 ~ 3389