低频振荡激励下呼吸阻抗测量的变分模态分解降噪方法研究  被引量:2

Research on denoising with variational mode decomposition for the measurement of respiratory impedance under low-frequency oscillation

在线阅读下载全文

作  者:车波 贲鸿伟 朱霖霖 刘磊 邓林红 CHE Bo;BEN Hongwei;ZHU Linlin;LIU Lei;DENG Linhong(Institute of Biomedical Engineering and Health Science,Changzhou University,Changzhou 213164,China;School of Information Science and Engineering,Changzhou University,Changzhou 213164)

机构地区:[1]常州大学生物医学工程与健康科学研究院,常州213164 [2]常州大学信息科学与工程学院,常州213164

出  处:《生物医学工程研究》2020年第3期231-236,共6页Journal Of Biomedical Engineering Research

基  金:国家自然科学基金资助项目(11532003,31670950)。

摘  要:强迫振荡技术(forced oscillation technique,FOT)的肺功能检查方法具有无创、快速和配合要求低等特点。针对在低频振荡(<5 Hz)的激励下,FOT可提供更丰富的小气道阻抗信息,但同时会产生非线性阻抗系统下的频带混叠干扰等问题,我们研究了变分模态分解(VMD)方法在呼吸阻抗测量中对呼吸压力和流量信号的自适应分解与降噪效果,并与经验模态分解(EMD)方法的降噪效果进行了比较。结果表明,VMD方法能更好地降低低频激励下的频带混叠和非平稳噪声影响,尤其对信号低频段的分解更为稳定和有效。该方法从信号降噪处理的角度,为低频激励下精准测量小气道阻抗提供了进一步研究的基础。Forced oscillation technique(FOT)has the characteristics of non-invasive,fast and requiring low level cooperation for pulmonary function test.FOT can provide more information about small airway impedance when measured at low-frequencies(<5 Hz).However,low measurement frequencies can cause band aliasing interference in the non-linear systems.To deal with this problem,we evaluated variational mode decomposition(VMD)in denoising the respiratory pressure and flow signals of respiratory impedance measurement under low-frequency oscillation,and compared the performance of VMD with that of the empirical mode decomposition(EMD)for respiratory impedance measurement at low-frequency oscillation.The results showed that compared to EMD,the VMD method could efficiently reduce the band aliasing interference and the non-stationary noise at low frequencies,and was more robust for signal decomposition in low-frequency range.From the perspective of signal noise reduction,it provides a basis for further exploring the accurate measurement of small airway impedance at low frequencies.

关 键 词:VMD算法 强迫振荡技术 低频振荡 小气道阻抗 非线性系统 

分 类 号:R318[医药卫生—生物医学工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象