Estimation of central pulse wave velocity from radial pulse wave analysis

被引:9
|
作者
Yao, Yang [1 ,2 ]
Zhou, Shuran [2 ]
Alastruey, Jordi [3 ,4 ]
Hao, Liling [2 ]
Greenwald, Stephen E. [5 ]
Zhang, Yuelan [6 ]
Xu, Lin [1 ]
Xu, Lisheng [2 ,7 ]
Yao, Yudong [8 ]
机构
[1] ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China
[2] Northeastern Univ, Coll Med & Biol Informat Engn, Shenyang 110169, Liaoning, Peoples R China
[3] Kings Coll London, Dept Biomed Engn, London SE1 7EH, England
[4] Sechenov Univ, World Class Res Ctr, Digital Biodesign & Personalized Healthcare, Moscow, Russia
[5] Queen Mary Univ London, Barts & London Sch Med & Dent, Blizard Inst, London, England
[6] China Med Univ, Hosp 1, Shenyang 110122, Liaoning, Peoples R China
[7] Neusoft Res Intelligent Healthcare Technol Co Ltd, Shenyang 110169, Liaoning, Peoples R China
[8] Stevens Inst Technol, Dept Elect & Comp Engn, Hoboken, NJ 07030 USA
基金
中国国家自然科学基金;
关键词
Arterial stiffness; Pulse wave analysis; Pulse wave velocity; Wave separation analysis; EXPERT CONSENSUS DOCUMENT; ARTERIAL STIFFNESS; CARDIOVASCULAR EVENTS; TRANSIT-TIME; PRESSURE; REFLECTION; QUANTIFICATION; VALIDATION; PREDICTION; DATABASE;
D O I
10.1016/j.cmpb.2022.106781
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Background and Objective: Arterial stiffness, commonly assessed by carotid-femoral pulse wave velocity (cfPWV), is an independent biomarker for cardiovascular disease. The measurement of cfPWV, however, has been considered impractical for routine clinical application. Pulse wave analysis using a single pulse wave measurement in the radial artery is a convenient alternative. This study aims to identify pulse wave features for a more accurate estimation of cfPWV from a single radial pulse wave measurement. Methods: From a dataset of 140 subjects, cfPWV was measured and the radial pulse waveform was recorded for 30 s twice in succession. Features were extracted from the waveforms in the time and frequency domains, as well as by wave separation analysis. All-possible regressions with bootstrapping, McHenry's select algorithm, and support vector regression were applied to compute models for cfPWV estimation. Results: The correlation coefficients between the measured and estimated cfPWV were r = 0.81, r = 0.81, and r = 0.8 for all-possible regressions, McHenry's select algorithm, and support vector regression, respectively. The features selected by all-possible regressions are physiologically interpretable. In particular, the amplitude ratio of the diastolic peak to the notch of the radial pulse waveform (R-n,d(r,P)) is shown to be correlated with cfPWV. This correlation was further evaluated and found to be independent of wave reflections using a dataset (n = 3,325) of simulated pulse waves. Conclusions: The proposed method may serve as a convenient surrogate for the measurement of cfPWV. R-n,d(r,P) is associated with aortic pulse wave velocity and this association may not be dependent on wave reflection. (C) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页数:12
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