Development of a Mathematical Model for Age-Dependent Radial Artery Pulse Wave Analysis Based on Pulse Waveform Decompositionopen access
- Authors
- Jo, Gwanghyun; Yang, Tae-Heon; Kim, Jaeuk U.; Koo, Jeong-Hoi; Kim, Young-Min
- Issue Date
- Dec-2019
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Age-dependent; hemodynamic; radial artery pulse waveform; wave decomposition; wave reflection model
- Citation
- IEEE Access, v.8, pp 2963 - 2974
- Pages
- 12
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE Access
- Volume
- 8
- Start Page
- 2963
- End Page
- 2974
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/115191
- DOI
- 10.1109/ACCESS.2019.2962300.
- ISSN
- 2169-3536
- Abstract
- Radial artery pulse waveforms (RAPWs) have been actively studied for decades because they provide critical health information, particularly related to risk factors of cardiovascular disease. The primary goal of this study is to develop a novel mathematical model that can regenerate age-dependent RAPWs by decomposing a single pulse pressure waveform (PPW). This study proposes to decompose a PPW into three waveform components with one forward wave component and two reflected wave components based on the physiology of pulse waveforms. Treated as basis functions, the three components with associated control parameters are incorporated in the proposed mathematical model. The underlying idea of the model is to generate desired pulse waveforms by combining basis functions whose characteristics depend on selection of control parameter values. For the current study, after determining the nine control parameters of the basis functions by post-processing algorithms, the proposed model for the PPW is derived from a linear combination of the basis functions. Using the model along with in vivo RAPW data, this study evaluates the performance of the model in regenerating PPWs for a wide range of ages from 85 years old to 15 years old. The results show an error of less than 6% between the PPWs numerically derived from the model and the in vivo data for the two key matrixes used in this study (the least-square error norm and the radial augmentation index), validating the effectiveness of the model. The model is applicable for RAPW simulator analysis and development. © 2013 IEEE.
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