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dc.contributor.author장준혁-
dc.date.accessioned2017-04-05T06:20:52Z-
dc.date.available2017-04-05T06:20:52Z-
dc.date.issued2015-07-
dc.identifier.citationCOMPUTERS IN BIOLOGY AND MEDICINE, v. 62, NO 1, Page. 154-163en_US
dc.identifier.issn0010-4825-
dc.identifier.issn1879-0534-
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S001048251500133X-
dc.identifier.urihttp://hdl.handle.net/20.500.11754/26599-
dc.description.abstractBackground: Current oscillometric blood pressure measurement devices generally provide only single-point estimates for systolic and diastolic blood pressures and rarely provide confidence ranges for these estimates. A novel methodology to obtain confidence intervals (CIs) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimates from a single oscillometric blood pressure measurement is presented. Methods: The proposed methodology utilizes the multiple regression technique to fuse optimally a set of SBP and DBP estimates obtained through different algorithms. However, the set of SBP and DBP estimates is a small number to determine the Cl of each individual subject. To address this issue, the weighted bootstrap approach based on the multiple regression technique was used to generate a pseudo sample set for the SBP and the DBP. In this paper, the multiple regression technique can estimate the best-fitting surface of an efficient function that relates the input sample set as an independent vector to the auscultatory nurse measurement as a dependent vector to estimate regression coefficients. Consequently, the coefficients are assigned to an eight-sample set obtained from the fusion of different algorithms as optimally weighted parameters. CIs are also estimated using the conventional methods on the set of fused SBP and DBP estimates for comparison purposes. Results: The proposed method was applied to an experimental dataset of 85 patients. The results indicated that the proposed approach provides better blood pressure estimates than the existing algorithms and, in addition, is able to provide CIs for a single measurement. Conclusions: The CIs derived from the proposed scheme are much smaller than those calculated by conventional methods except for the pseudo maximum amplitude-envelope algorithm for both the SBP and the DBP, probably because of the decrease in the standard deviation through the increase in the pseudo measurements using the weighted bootstrap method for each subject. The proposed methodology is likely the only one currently available that can provide as for single-sample blood pressure measurements. (C) 2015 Elsevier Ltd. All rights reserved.en_US
dc.description.sponsorshipWe wish to further thank Biosign Technologies Inc. for providing us with equipment and data. This research was supported by NRF (2014R1A2A1A10049735) and also this research was supported by NRF (14035195). We also thank to two independent trained observers (nurses), who obtained the blood pressure measurement.en_US
dc.language.isoenen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.subjectBlood pressureen_US
dc.subjectOscillometric blood pressure measurementen_US
dc.subjectConfidence intervalen_US
dc.subjectParametric bootstrapen_US
dc.subjectFusionen_US
dc.subjectMultiple regressionen_US
dc.titleEstimated confidence interval from single blood pressure measurement based on algorithmic fusionen_US
dc.typeArticleen_US
dc.relation.no1-
dc.relation.volume62-
dc.identifier.doi10.1016/j.compbiomed.2015.04.015-
dc.relation.page154-163-
dc.relation.journalCOMPUTERS IN BIOLOGY AND MEDICINE-
dc.contributor.googleauthorLee, Soojeong-
dc.contributor.googleauthorRajan, Sreeraman-
dc.contributor.googleauthorPark, Chee-Hyun-
dc.contributor.googleauthorChang, Joon-Hyuk-
dc.contributor.googleauthorDajani, Hilmi R.-
dc.contributor.googleauthorGroza, Voicu Z.-
dc.relation.code2015003086-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF ELECTRONIC ENGINEERING-
dc.identifier.pidjchang-
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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