Quantitative analysis of pulse arrival time and PPG morphological features based cuffless blood pressure estimation: a comparative study between diabetic and non-diabetic groups
- Authors
- Park, Seongryul; Lee, Seungjae; Park, Eunkyoung; Lee, Jongshill; Kim, In Young
- Issue Date
- Nov-2023
- Publisher
- 대한의용생체공학회
- Keywords
- Cuffless blood pressure estimation; Pulse arrival time; PPG morphological features; Relative feature importance; Diabetes
- Citation
- Biomedical Engineering Letters (BMEL), v.13, no.4, pp 625 - 636
- Pages
- 12
- Journal Title
- Biomedical Engineering Letters (BMEL)
- Volume
- 13
- Number
- 4
- Start Page
- 625
- End Page
- 636
- URI
- https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/25324
- DOI
- 10.1007/s13534-023-00284-w
- ISSN
- 2093-9868
2093-985X
- Abstract
- Pulse arrival time (PAT) and PPG morphological features have attracted much interest in cuffless blood pressure (BP) estimation, but their effects are not clearly understood when vascular characteristics are affected by diseases such as diabetes. This work quantitatively analyzes the effect of diabetic disease on the PAT and PPG morphological features-based BP estimation. We selected 112 diabetic patients and 308 non-diabetic subjects from VitalDB, and extracted 16 features including PAT, PPG morphological features, and heart rate. BP estimation performance was statistically compared between groups using linear regression models with several feature sets, and the relative importance of each feature in the optimal feature set was extracted. As a result, the standard deviation of the error and mean absolute error of PAT-based BP estimation were significantly higher in the diabetic group than in the non-diabetic group (p < 0.01). A feature set containing PAT and PPG morphological features achieved the best performance in both groups. However, the relative importance of each feature for BP estimation differed notably between groups. The results indicate that different features are important depending on the vascular characteristics, which could help to construct different models to accommodate specific diseases.
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Collections - College of Medical Sciences > Department of Biomedical Mechatronics > 1. Journal Articles
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