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Title:: Study on method of extracting respiratory wave from photoplethys-mography signals using empirical mode decomposition algorithm

作者:: 陈真诚1△; 牛春望1; 朱健铭2; 梁永波1; 1.桂林电子科技大学电子工程与自动化学院，广西桂林 541004；2.桂林电子科技大学生命与环境科学学院，广西桂林 541004

Author(s):: CHEN Zhencheng1; NIU Chunwang1; ZHU Jianming2; LIANG Yongbo1; 1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China; 2. School of Life and Environmental Science, Guilin University of Electronic Technology, Guilin 541004

Keywords:: Photoplethysmography; Empirical mode decomposition(EMD); MIMIC Database; Intrinsic mode function(IMF); Respiratory signal

摘要:: 针对目前提取呼吸波准确性不高的问题，本研究提出了一种从光电容积描记（photoplethysmography， PPG）信号中提取呼吸波的有效方法。在MIMIC Database中获取人体同时段的多路生理信号，包括PPG信号和呼吸波信号。首先，利用经验模态分解算法（empirical mode decomposition ，EMD）对PPG信号进行分解，得到各层本征模函数（intrinsic mode function，IMF），选择合适的IMF分量重构出呼吸波信号；然后将重构的呼吸波信号与采用PPG信号同时段的原始呼吸波信号进行比较，结果显示，呼吸波信号速率的准确率均在90%以上，AR功率谱中的相关性系数均在85%以上，呼吸波信号相对相干系数也显示该方法的优越性。采用EMD算法可以有效地从PPG信号中提取呼吸波，这对于临床实践中的无创检测，医疗设备的改进具有重要意义。

Abstract:: To present an efficient method for extracting respiratory wave from the photoplethysmography (PPG) signals of human fingertip in order to solve the problem with low accuracy of extracting respiratory wave at present. Multiple physiological signals of the human body at the same time in the MIMIC Database were obtained，including the PPG signals and the respiratory wave signals. Firstly, PPG signals were decomposed using the empirical mode decomposition (EMD) algorithm to obtain the intrinsic mode functions (IMF) of each layer, selecting the appropriate IMF component to reconstruct the respiratory wave signals. Then, the reconstructed respiratory wave signals were compared with the original respiratory wave signals at the same time of the PPG signals. The results showed that the accuracy of the respiratory wave signals rate was above 90% and the correlation coefficient in the AR power spectrum was above 85%，the evaluated relative coherence coefficient of the respiratory wave signals had shown the superiority of the method. The EMD algorithm can effectively extract the respiratory wave signals from the PPG signals, which is of great significance for the non-invasive detection in clinical practice and the improvement of medical equipment.