A Knowledge-Based Approach to Arterial Stiffness Estimation Using the Digital Volume Pulse

We have developed a knowledge based approach for arterial stiffness estimation. The proposed new approach reliably estimates arterial stiffness based on the analysis of age and heart rate normalized reflected wave arrival time. The proposed new approach reduces cost, space, technical expertise, spec...

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Bibliographic Details
Published inIEEE transactions on biomedical circuits and systems Vol. 6; no. 4; pp. 366 - 374
Main Authors Dae-Geun Jang, Farooq, U., Seung-Hun Park, Choong-Won Goh, Minsoo Hahn
Format Journal Article
LanguageEnglish
Published United States IEEE 01.08.2012
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Ankle Brachial Index
Arterial stiffness
Arteries - pathology
Biomedical Engineering
Biomedical measurements
Blood Pressure
cardiovascular disease
Computers
Correlation
digital volume pulse
Electrocardiography
Electronics
Equipment Design
Estimation
Feature extraction
Female
Heart Rate
Humans
Hypertension
Linear Models
Male
Photoplethysmography - instrumentation
Pulse
pulse contour analysis
Pulse Wave Analysis
Reproducibility of Results
Signal detection
Signal Processing, Computer-Assisted
Studies
Training
Vascular Stiffness
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Summary:We have developed a knowledge based approach for arterial stiffness estimation. The proposed new approach reliably estimates arterial stiffness based on the analysis of age and heart rate normalized reflected wave arrival time. The proposed new approach reduces cost, space, technical expertise, specialized equipment, complexity, and increases the usability compared to recently researched noninvasive arterial stiffness estimators. The proposed method consists of two main stages: pulse feature extraction and linear regression analysis. The new approach extracts the pulse features and establishes a linear prediction equation. On evaluating proposed methodology with pulse wave velocity (PWV) based arterial stiffness estimators, the proposed methodology offered the error rate of 8.36% for men and 9.52% for women, respectively. With such low error rates and increased benefits, the proposed approach could be usefully applied as low cost and effective solution for ubiquitous and home healthcare environments.
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ISSN:1932-4545
1940-9990
DOI:10.1109/TBCAS.2011.2177835