[1]李勋,刘丽荣,李浩,等.基于PPG信号的极简特征回归树血压估计模型设计[J].中国医学物理学杂志,2024,41(6):769-775.[doi:DOI:10.3969/j.issn.1005-202X.2024.06.016]
　LI Xun,LIU Lirong,LI Hao,et al.Regression tree model for blood pressure estimation using the minimalist characteristics of photoplethysmography signal[J].Chinese Journal of Medical Physics,2024,41(6):769-775.[doi:DOI:10.3969/j.issn.1005-202X.2024.06.016]
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基于PPG信号的极简特征回归树血压估计模型设计()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
41卷
期数:
2024年第6期
页码:
769-775
栏目:
医学信号处理与医学仪器
出版日期:
2024-06-25

文章信息/Info

Title:
Regression tree model for blood pressure estimation using the minimalist characteristics of photoplethysmography signal
文章编号:
1005-202X（2024）06-0769-07
作者:
李勋1; 刘丽荣1; 李浩2; 杨怜琳3; 王志敏3; 邹梅1
1.昆明学院物理科学与技术学院， 云南 昆明 650214； 2.昆明学院医学院， 云南 昆明 650214； 3.昆明市延安医院， 云南 昆明 650051
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
关键词:
光电容积脉搏波; 极简特征; 斯皮尔曼相关系数; 血压估计模型
Keywords:
Keywords: photoplethysmography minimalist characteristics Spearman correlation coefficient blood pressure estimation model
分类号:
R318；Q632
DOI:
DOI:10.3969/j.issn.1005-202X.2024.06.016
文献标志码:
A
摘要:
目的：提出一种基于光电容积脉搏波（PPG）的极简特征回归树血压估计模型。方法：从单路PPG信号中提取15个特征参数，利用斯皮尔曼相关系数筛选与血压相关性最高的4个参数，构建极简特征回归树血压模型。结果：极简特征回归树血压模型收缩压和舒张压的估计误差分别达到（-0.02±3.63） mmHg和（-0.04±2.10） mmHg。结论：提出的极简特征回归树血压模型结构简洁、准确率较高，这一发现对于在可穿戴设备中使用单路PPG信号进行血压估计具有重要意义。
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.

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备注/Memo

备注/Memo:
【收稿日期】2024-02-25 【基金项目】昆明学院引进人才科研项目（XJ20210003）；云南省科技厅基础研究计划（ZX20240033） 【作者简介】李勋，硕士，研究方向：医学信号处理，E-mail: 973338674@qq.com 【通信作者】邹梅，高级工程师，研究生导师，研究方向：医学信号处理以及光电传感器，E-mail: bill_zom@126.com
更新日期/Last Update: 2024-06-25