首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于光电容积脉搏波的无创血压连续测量研究进展
引用本文:叶青,章祎枫,沙金亮,方桦,余瑛.基于光电容积脉搏波的无创血压连续测量研究进展[J].科学技术与工程,2024,24(5):1756-1774.
作者姓名:叶青  章祎枫  沙金亮  方桦  余瑛
作者单位:江西中医药大学计算机学院;南昌大学教育技术与教学资源中心
基金项目:江西中医药大学校级科技创新团队发展计划 (团队编号:CXTD22015)
摘    要:在临床诊断过程中,血压能够反映患者血液流动、身体体征变化等生理信息,是诊断组织器官健康状态的重要参考数据。由于传统血压测量方法存在有创、间断等局限性,利用光电容积脉搏波描记法(photo plethysmo graphy, PPG)实现血压的无创连续检测成为当前血压测量的热门研究领域。为此,首先简要介绍了PPG的理论背景与技术原理;其次阐述了利用PPG进行血压预测的具体流程,包括公开数据集、评估标准、预处理方法、特征提取与模型建立,并就不同方法的优缺点进行了对比分析;最后,总结了基于PPG实现无创血压连续测量的挑战与未来研究方向,为今后的研究提供参考。

关 键 词:光电容积脉搏波  血压监测  特征提取  深度学习
收稿时间:2023/5/30 0:00:00
修稿时间:2024/2/12 0:00:00

Research Progress of Non-Invasive Blood Pressure Continuous Measurement Based on PhotoPlethysmoGraphy
Ye Qing,Zhang Yifeng,Sha Jinliang,Fang Hu,Yu Ying.Research Progress of Non-Invasive Blood Pressure Continuous Measurement Based on PhotoPlethysmoGraphy[J].Science Technology and Engineering,2024,24(5):1756-1774.
Authors:Ye Qing  Zhang Yifeng  Sha Jinliang  Fang Hu  Yu Ying
Institution:School of Computer Science, Jiangxi University of Chinese Medicine
Abstract:In the clinical diagnostic process, blood pressure is a crucial parameter that serves as a key reference for assessing blood flow dynamics and health status. Basing PhotoPlethysmoGraphy (PPG) for non-invasive continuous blood pressure monitoring has been a surge of interest in the research field, due to the limitations of traditional blood pressure measurements, such as invasiveness and intermittency. In this article, theoretical background and technical principles of PPG are briefly introduced. Subsequently, the specific processes including open datasets, evaluation standards, prepossessing methods, feature extraction, and model establishment, are comprehensively discussed, compared analysis of the advantages and disadvantages of different methods is conducted. Finally, the challenges and future research directions in achieving non-invasive continuous blood pressure measurement based on PPG are summarized, with the aim of providing guidance for future research endeavors.
Keywords:photoplethysmography  blood pressure monitoring  feature extraction  deep learning
点击此处可从《科学技术与工程》浏览原始摘要信息
点击此处可从《科学技术与工程》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号