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
- 장준혁
- Keywords
- Gaussian mixture regression (GMR); oscillometric blood pressure estimation; 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/20.500.11754/45748
- ISSN
- 0018-9456
- DOI
- 10.1109/TIM.2013.2273612
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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