Regression tree model for blood pressure estimation using the minimalist characteristics of photoplethysmography signal(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2024年第6期
- Page:
- 769-775
- Research Field:
- 医学信号处理与医学仪器
- Publishing date:
Info
- Title:
- Regression tree model for blood pressure estimation using the minimalist characteristics of photoplethysmography signal
- Author(s):
- LI Xun1; LIU Lirong1; LI Hao2; YANG Lianlin3; WANG Zhimin3; ZOU Mei1
- 1. School of Physical Science and Technology, Kunming University, Kunming 650214, China 2. School of Medicine, Kunming University, Kunming 650214, China 3. Yanan Hospital of Kunming City, Kunming 650051, China
- Keywords:
- Keywords: photoplethysmography minimalist characteristics Spearman correlation coefficient blood pressure estimation model
- PACS:
- R318；Q632
- DOI:
- DOI:10.3969/j.issn.1005-202X.2024.06.016
- Abstract:
- Abstract: Objective To propose a regression tree model for the estimation of blood pressure using the minimalist characteristics of photoplethysmography (PPG) signals. Methods Fifteen characteristic parameters were extracted from the PPG signals, and the 4 parameters with the highest correlations with blood pressure were screened using the Spearman correlation coefficient to construct a regression tree model for blood pressure estimation using the minimalist characteristics. Results The estimation errors of systolic and diastolic blood pressures in the constructed model were (-0.02±3.63) mmHg and (-0.04±2.10) mmHg, respectively. Conclusion The proposed regression tree model has a simple structure and high accuracy, which is of great significance for using a single-channel PPG signal for blood pressure estimation in wearable devices.
Last Update: 2024-06-25