Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 이수정 | - |
dc.date.accessioned | 2018-03-24T01:30:30Z | - |
dc.date.available | 2018-03-24T01:30:30Z | - |
dc.date.issued | 2013-10 | - |
dc.identifier.citation | Sensors (Basel, Switzerland), 2013, 13(10), P.13609-13623 | en_US |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | http://www.mdpi.com/1424-8220/13/10/13609/ | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/51705 | - |
dc.description.abstract | The maximum amplitude algorithm (MAA) is generally utilized in the estimation of the pressure values, and it uses heuristically obtained ratios of systolic and diastolic oscillometric amplitude to the mean arterial pressure (known as systolic and diastolic ratios) in order to estimate the systolic and diastolic pressures. This paper proposes a Bayesian model to estimate the systolic and diastolic ratios. These ratios are an improvement over the single fixed systolic and diastolic ratios used in the algorithms that are available in the literature. The proposed method shows lower mean difference (MD) with standard deviation (SD) compared to the MAA for both SBP and DBP consistently in all the five measurements. | en_US |
dc.description.sponsorship | The authors thank Biosign for providing equipment and data. The authors would like to thank Hilmi Dajani, Voicu Groza, Miodrag Bolic, and Sreeraman Rajan who are with the School of Electrical and Computer Science, University of Ottawa, Canada. This research was supported by NRF(2013R1A1A2012536). This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning(2013R1A1A1010797) | en_US |
dc.language.iso | en | en_US |
dc.publisher | MDPI AG, POSTFACH, CH-4005 BASEL, SWITZERLAND | en_US |
dc.subject | oscillometric blood pressure estimation | en_US |
dc.subject | systolic and diastolic ratios | en_US |
dc.subject | Bayesian model | en_US |
dc.subject | maximum amplitude algorithm | en_US |
dc.subject | VARIABILITY | en_US |
dc.subject | ERROR | en_US |
dc.title | On using Maximum Amplitude a Posteriori Probability based on a Bayesian Model for Oscillometric Blood Pressure Estimation | en_US |
dc.type | Article | en_US |
dc.relation.no | 10 | - |
dc.relation.volume | 13 | - |
dc.identifier.doi | 10.3390/s131013609 | - |
dc.relation.page | 13609-13623 | - |
dc.relation.journal | SENSORS | - |
dc.contributor.googleauthor | Lee, Soojeong | - |
dc.contributor.googleauthor | Jeon, Gwanggil | - |
dc.contributor.googleauthor | Lee, Gangseong | - |
dc.relation.code | 2013007838 | - |
dc.sector.campus | S | - |
dc.sector.daehak | INDUSTRY-UNIVERSITY COOPERATION FOUNDATION[S] | - |
dc.sector.department | RESEARCH INSTITUTE | - |
dc.identifier.pid | leesoo86 | - |
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