A Meta-Analysis of Pulse Arrival Time Based Blood Pressure Estimation - Publication - Bridge of Knowledge

Search

A Meta-Analysis of Pulse Arrival Time Based Blood Pressure Estimation

Abstract

The paper presents a preliminary meta-analysis of the sample correlation between pulse arrival time (PAT) and blood pressure (BP). The aim of the study was to verify sample correlation coefficient between PAT and BP using an affine model BP = a · P AT + b for systolic and diastolic blood pressure. The databases included in the search were the IEEE Xplore Digital Library, Springer Link and Google Scholar. Only papers from 2005 to 2017 were included into analysis. The random-effects model was considered. The resulting sample correlation coefficient was equal to -0.82 (95 % CI; -0.89, -0.72) for systolic blood pressure and -0.64 (95% CI, -0.74 -0.51) for diastolic one. Egger’s regression test showed that there was no evidence of publication bias. Obtained 95% CI intervals for sample correlation coefficients for SBP and DBP are almost separate, which may indicate different relation between PAT and BP for systolic and diastolic pressure

Citations

  • 2

    CrossRef

  • 0

    Web of Science

  • 3

    Scopus

Cite as

Full text

full text is not available in portal

Keywords

Details

Category:
Conference activity
Type:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Title of issue:
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) strony 5822 - 5825
Language:
English
Publication year:
2018
Bibliographic description:
Poliński A., Pietrewicz M., Kocejko T., Bujnowski A., Rumiński J., Wtorek J.: A Meta-Analysis of Pulse Arrival Time Based Blood Pressure Estimation// 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)/ Honolulu, HI, USA: , 2018, s.5822-5825
DOI:
Digital Object Identifier (open in new tab) 10.1109/embc.2018.8513605
Verified by:
Gdańsk University of Technology

seen 101 times

Recommended for you

Meta Tags