Literature DB >> 22147332

Subject-specific estimation of central aortic blood pressure using an individualized transfer function: a preliminary feasibility study.

Jin-Oh Hahn1, Andrew T Reisner, Farouc A Jaffer, H Harry Asada.   

Abstract

This paper presents a new approach to the estimation of unknown central aortic blood pressure waveform from a directly measured peripheral blood pressure waveform, in which a physics-based model is employed to solve for a subject- and state-specific individualized transfer function (ITF). The ITF provides the means to estimate the unknown central aortic blood pressure from the peripheral blood pressure. Initial proof-of-principle for the ITF is demonstrated experimentally through an in vivo protocol. In swine subjects taken through wide range of physiologic conditions, the ITF was on average able to provide central aortic blood pressure waveforms more accurately than a nonindividualized transfer function. Its usefulness was most evident when the subject's pulse transit time deviated from normative values. In these circumstances, the ITF yielded statistically significant reductions over a nonindividualized transfer function in the following three parameters: 1) 30% reduction in the root-mean-squared error between estimated versus actual central aortic blood pressure waveform (p < 10 (-4)), 2) >50% reduction in the error between estimated versus actual systolic and pulse pressures ( p < 10 (-4)), and 3) a reduction in the overall breakdown rate (i.e., the frequency of estimation errors >3 mmHg, p < 10 (-4)). In conclusion, the ITF may offer an attractive alternative to existing methods that estimates the central aortic blood pressure waveform, and may be particularly useful in nonnormative physiologic conditions.
© 2012 IEEE

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Year:  2011        PMID: 22147332     DOI: 10.1109/TITB.2011.2177668

Source DB:  PubMed          Journal:  IEEE Trans Inf Technol Biomed        ISSN: 1089-7771


  6 in total

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Journal:  Front Physiol       Date:  2021-02-23       Impact factor: 4.566

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  6 in total

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