[1]陈真诚,宋浩,朱健铭,等. 基于光电容积脉搏波的呼吸监测系统研究[J].中国医学物理学杂志,2019,36(5):579-584.[doi:DOI:10.3969/j.issn.1005-202X.2019.05.017]
 CHEN Zhencheng,SONG Hao,ZHU Jianming,et al. Respiration monitoring system based on photolethysmography[J].Chinese Journal of Medical Physics,2019,36(5):579-584.[doi:DOI:10.3969/j.issn.1005-202X.2019.05.017]
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 基于光电容积脉搏波的呼吸监测系统研究()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
36卷
期数:
2019年第5期
页码:
579-584
栏目:
医学信号处理与医学仪器
出版日期:
2019-05-25

文章信息/Info

Title:
 Respiration monitoring system based on photolethysmography
文章编号:
1005-202X(2019)05-0579-06
作者:
 陈真诚1宋浩2朱健铭1梁永波1
 1.桂林电子科技大学生命与环境科学学院, 广西 桂林 541004; 2.桂林电子科技大学电子工程与自动化学院, 广西 桂林 541004
Author(s):
 CHEN Zhencheng1 SONG Hao2 ZHU Jianming1 LIANG Yongbo1
 1. School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China; 2. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China
关键词:
 光电容积脉搏波呼吸信号呼吸频率红外光光电脉搏传感器
Keywords:
 Keywords: photoplethysmography respiratory signal respiratory rate infrared light photoelectric pulse sensor
分类号:
R318;Q819
DOI:
DOI:10.3969/j.issn.1005-202X.2019.05.017
文献标志码:
A
摘要:
 通过研究人体指端光电容积脉搏波(PPG)的物理特性,以朗伯比尔定律为基本原理,通过设计硬件电路,实现对人体PPG的无创采集。对采集到的PPG信号进行滤波和放大处理,通过特征选择和提取等方式识别出比较完整的脉搏波信号;将得到的脉搏波信号进行经验模态分解,选择具有适当频率的本征模函数重构出待测的呼吸波信号,并在显示屏上显示出来。在采集脉搏波的同时利用迈瑞公司的PM-9000 Express病人监护仪对人体的呼吸信号进行采集。本系统采集了10例志愿者数据。将本系统得到的呼吸波信号与病人监护仪测得呼吸波进行频谱分析,并对相关参数进行比较,发现两种呼吸波具有较好的相关性。本文最终结果表明利用经验模态分解方法提取人体PPG中包含的呼吸信号具有较好的准确性和可行性。实验结果表明这种方法可以从PPG中提取呼吸信号。
Abstract:
 Abstract: The physical characteristics of the photoplethysmography (PPG) pulse waves of human fingers are investigated in this study and a hardware circuit is designed based on Lambert’s law to realize the non-invasive acquisition of human PPG pulse waves. After the collected PPG pulse wave signals are filtered and amplified, the complete pulse wave signals are identified through feature selection and extraction. Subsequently, the obtained pulse wave signals are processed with empirical mode decomposition, and an eigenmode function with an appropriate frequency is adopted to reconstruct the respiratory wave signals to be measured and display the signals on the screen. Meanwhile, the respiratory signals of the human body are collected with PM-9000 Express patient monitor (Mindray). The data of 10 volunteers are also collected with the system. The spectral analysis between the respiratory wave signals obtained by the proposed system and the signals measured by the patient monitor and the analysis of the related parameters showed that the two kinds of respiratory waves have a good correlation. The final result of this study reveals that using empirical mode decomposition to extract the respiratory signals contained in the PPG pulse waves of human fingers is proved to be accurate and feasible. The proposed method can be used to extract respiratory signals from PPG pulse waves.

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备注/Memo

备注/Memo:
 【收稿日期】2018-11-25
【基金项目】国家自然科学基金重大科研仪器研制项目(61627807);广西自然科学基金(2017GXNSFGA198005);国家重点研发计划课题(2016YFC1305703);广西自然科学基金青年基金项目(2016GXNSFBA380145);广西自动检测技术与仪器重点实验室主任基金(YQ17118);广西信息科学实验中心一般项目(YB1513)
【作者简介】陈真诚,博士,教授,博士生导师,主要研究方向为生物传感与智能仪器、信号与信息处理、医学成像与图像处理、生物制造、环境监测及仪器,E-mail: 18078842451@163.com
【通信作者】朱健铭,博士,副教授,硕士生导师,研究方向为生物传感与智能仪器、生物医学信号处理,E-mail: zjmcsu@126.com
更新日期/Last Update: 2019-05-23