Estimation of cardiovascular risk predictors from non-invasively measured diametric pulse volume waveforms via multiple measurement information fusion

Zahra Ghasemi, Jong Chan Lee, Chang Sei Kim, Hao Min Cheng, Shih Hsien Sung, Chen Huan Chen, Ramakrishna Mukkamala, Jin Oh Hahn*

*此作品的通信作者

研究成果: Article同行評審

25 引文 斯高帕斯(Scopus)

摘要

This paper presents a novel multiple measurement information fusion approach to the estimation of cardiovascular risk predictors from non-invasive pulse volume waveforms measured at the body's diametric (arm and ankle) locations. Leveraging the fact that diametric pulse volume waveforms originate from the common central pulse waveform, the approach estimates cardiovascular risk predictors in three steps by: (1) deriving lumped-parameter models of the central-diametric arterial lines from diametric pulse volume waveforms, (2) estimating central blood pressure waveform by analyzing the diametric pulse volume waveforms using the derived arterial line models, and (3) estimating cardiovascular risk predictors (including central systolic and pulse pressures, pulse pressure amplification, and pulse transit time) from the arterial line models and central blood pressure waveform in conjunction with the diametric pulse volume waveforms. Experimental results obtained from 164 human subjects with a wide blood pressure range (systolic 144 mmHg and diastolic 103 mmHg) showed that the approach could estimate cardiovascular risk predictors accurately (r ≥ 0.78). Further analysis showed that the approach outperformed a generalized transfer function regardless of the degree of pulse pressure amplification. The approach may be integrated with already available medical devices to enable convenient out-of-clinic cardiovascular risk prediction.

原文English
文章編號10433
期刊Scientific reports
8
發行號1
DOIs
出版狀態Published - 1 12月 2018

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