基于改进EEMD的呼吸波提取算法

发布时间：2018-01-11 09:16

  本文关键词：基于改进EEMD的呼吸波提取算法　出处：《科技通报》2017年01期 　论文类型：期刊论文

  更多相关文章： 改进EEMD 瞬时频率 呼吸波 容积脉搏波

【摘要】：针对人体指端的光电容积脉搏波(PPG)提取呼吸波的缺点,并根据PPG信号的特点提出一种改进的整体平均经验模态分解(EEMD)算法。该算法利用PPG信号次波峰幅度平均值来确定添加噪声强度,计算每层分解的平均瞬时频率,在减少分解层数的同时选取较好的固有模态函数(IMF)重构呼吸波。采用MIMIC数据库中的4组数据进行测试,得到波形相对相关系数在0.65以上,幅度平方相干系数在0.98以上。实验结果表明,本文算法不但克服了EEMD算法提取呼吸波添加噪声和循环次数的不准确性,而且可以更有效、更准确的提取PPG中的呼吸波。
[Abstract]:The drawback of extracting respiratory wave is the photoelectric volumetric pulse wave (PPG) of human finger. According to the characteristics of PPG signal, an improved global average empirical mode decomposition (EMD) algorithm is proposed, which uses the average of the sub-peak amplitude of PPG signal to determine the added noise intensity. The average instantaneous frequency of each decomposition layer is calculated and the respiratory wave is reconstructed by selecting a better inherent mode function (IMF) while reducing the number of decomposition layers. Four groups of data in the MIMIC database are used for testing. The relative correlation coefficient of waveform is above 0.65, and the squared coherence coefficient of amplitude is above 0.98. The experimental results show that the correlation coefficient is more than 0.65. The proposed algorithm not only overcomes the inaccuracy of the EEMD algorithm in extracting the respiratory wave adding noise and the number of cycles, but also can extract the respiratory wave from PPG more effectively and accurately.
【作者单位】： 北京信息科技大学通信工程系;
【基金】：国家科技重大专项煤层气田地面集输信息集成及深度开发技术(2011ZX05039-004-02) 北京信息科技大学研究生科技创新项目(5111524104)
【分类号】：R443.6;TN911.6
【正文快照】： 呼吸是人体生命体征的重要参数之一,也是危重病人首要的和持续的检测参数。目前,呼吸波信号通常使用呼吸量测定法等传统方法,这些方法不但会干扰患者的自然呼吸而且无法在压力测试、睡眠研究、家庭医疗等多种情况下使用。基于光电容积脉搏波(photoplethysmograph-ic,PPG)可以，

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