Literature DB >> 31653002

Analysis of Pulse Arrival Time as an Indicator of Blood Pressure in a Large Surgical Biosignal Database: Recommendations for Developing Ubiquitous Blood Pressure Monitoring Methods.

Joonnyong Lee1, Seungman Yang2, Saram Lee3, Hee Chan Kim4,5.   

Abstract

As non-invasive continuous blood pressure monitoring (NCBPM) has gained wide attraction in the recent decades, many pulse arrival time (PAT) or pulse transit time (PTT) based blood pressure (BP) estimation studies have been conducted. However, most of the studies have used small homogeneous subject pools to generate models of BP based on particular interventions for induced hemodynamic change. In this study, a large open biosignal database from a diverse group of 2309 surgical patients was analyzed to assess the efficacy of PAT, PTT, and confounding factors on the estimation of BP. After pre-processing the dataset, a total of 6,777,308 data pairs of BP and temporal features between electrocardiogram (ECG) and photoplethysmogram (PPG) were extracted and analyzed. Correlation analysis revealed that PAT or PTT extracted from the intersecting-tangent (IT) point of PPG showed the highest mean correlation to BP. The mean correlation between PAT and systolic blood pressure (SBP) was -0.37 and the mean correlation between PAT and diastolic blood pressure (DBP) was -0.30, outperforming the correlation between BP and PTT at -0.12 for SBP and -0.11 for DBP. A linear model of BP with a simple calibration method using PAT as a predictor was developed which satisfied international standards for automatic oscillometric BP monitors in the case of DBP, however, SBP could not be predicted to a satisfactory level due to higher errors. Furthermore, multivariate regression analyses showed that many confounding factors considered in previous studies had inconsistent effects on the degree of correlation between PAT and BP.

Entities:  

Keywords:  biosignal database; blood pressure monitoring; cardiovascular monitoring; hypertension; pulse arrival time; pulse transit time; pulse wave velocity; ubiquitous healthcare

Year:  2019        PMID: 31653002     DOI: 10.3390/jcm8111773

Source DB:  PubMed          Journal:  J Clin Med        ISSN: 2077-0383            Impact factor:   4.241


  5 in total

Review 1.  Cuffless Blood Pressure Monitoring: Academic Insights and Perspectives Analysis.

Authors:  Shiyun Li; Can Zhang; Zhirui Xu; Lihua Liang; Ye Tian; Long Li; Huaping Wu; Sheng Zhong
Journal:  Micromachines (Basel)       Date:  2022-07-30       Impact factor: 3.523

2.  Prognosis of Diabetic Peripheral Neuropathy via Decomposed Digital Volume Pulse from the Fingertip.

Authors:  Hai-Cheng Wei; Wen-Rui Hu; Na Ta; Ming-Xia Xiao; Xiao-Jing Tang; Hsien-Tsai Wu
Journal:  Entropy (Basel)       Date:  2020-07-09       Impact factor: 2.524

3.  Blood pressure altering method affects correlation with pulse arrival time.

Authors:  Sondre Heimark; Ole Marius H Rindal; Trine M Seeberg; Alexey Stepanov; Elin S Boysen; Kasper G Bøtker-Rasmussen; Nina K Mobæk; Camilla L Søraas; Aud E Stenehjem; Fadl Elmula M Fadl Elmula; Bård Waldum-Grevbo
Journal:  Blood Press Monit       Date:  2022-04-01       Impact factor: 1.444

4.  Blood Pressure Response and Pulse Arrival Time During Exercise Testing in Well-Trained Individuals.

Authors:  Sondre Heimark; Ingrid Eitzen; Isabella Vianello; Kasper G Bøtker-Rasmussen; Asgeir Mamen; Ole Marius Hoel Rindal; Bård Waldum-Grevbo; Øyvind Sandbakk; Trine M Seeberg
Journal:  Front Physiol       Date:  2022-07-11       Impact factor: 4.755

5.  Conventional pulse transit times as markers of blood pressure changes in humans.

Authors:  Robert C Block; Mohammad Yavarimanesh; Keerthana Natarajan; Andrew Carek; Azin Mousavi; Anand Chandrasekhar; Chang-Sei Kim; Junxi Zhu; Giovanni Schifitto; Lalit K Mestha; Omer T Inan; Jin-Oh Hahn; Ramakrishna Mukkamala
Journal:  Sci Rep       Date:  2020-10-02       Impact factor: 4.379

  5 in total

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