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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
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47초록
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, Soojeong; Chang, Joon-Hyuk; Nam, Sang Won; Lim, Chungsoo; Rajan, Sreeraman; Dajani, Hilmi R.; Groza, Voicu Z.
- 발행일
- 2013-12
- 유형
- Article
- 권
- 62
- 호
- 12
- 페이지
- 3387 ~ 3389