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

Title
Oscillometric Blood Pressure Estimation Based on Maximum Amplitude Algorithm Employing Gaussian Mixture Regression
Author
이수정
Keywords
Gaussian mixture regression (GMR); maximum amplitude algorithm (MAA); oscillometric blood pressure estimation
Issue Date
2013-12
Publisher
IEEE INSTITUTE OF ELECTRICAL AND ELECTRONICS
Citation
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, Vol.62, No.12 [2013], p3387-3389
Abstract
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.
URI
http://ieeexplore.ieee.org/document/6587819/http://hdl.handle.net/20.500.11754/45750
ISSN
0018-9456
DOI
10.1109/TIM.2013.2273612
Appears in Collections:
INDUSTRY-UNIVERSITY COOPERATION FOUNDATION[S](산학협력단) > ETC
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