|本期目录/Table of Contents|

[1]车波,贲鸿伟,朱霖霖,等.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*[J].生物医学工程研究,2020,03:231-236.
 CHE Bo,BEN Hongwei,ZHU Linlin,et al.Research on denoising with variational mode decomposition for the measurement of respiratory impedance under low-frequency oscillation[J].Journal of Biomedical Engineering Research,2020,03:231-236.
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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*(PDF)

《生物医学工程研究》[ISSN:1006-6977/CN:61-1281/TN]

期数:
2020年03期
页码:
231-236
栏目:
出版日期:
2020-09-25

文章信息/Info

Title:
Research on denoising with variational mode decomposition for the measurement of respiratory impedance under low-frequency oscillation
文章编号:
1672-6278 (2020)03-0231-06
作者:
车波12贲鸿伟12朱霖霖1刘磊1邓林红 1 △
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
Author(s):
CHE Bo12 BEN Hongwei12 ZHU Linlin1 LIU Lei1 DENG Linhong1
1. Institute of Biomedical Engineering and Health Science, Changzhou University, Changzhou 213164, China;2. School of Information Science and Engineering, Changzhou University, Changzhou 213164
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
Keywords:
Variational mode decomposition Forced oscillation technique Low-frequency oscillation Small airway impedance Non-linear system
分类号:
R318
DOI:
10.19529/j.cnki.1672-6278.2020.03.03
文献标识码:
A
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。
Abstract:
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.

参考文献/References

备注/Memo

备注/Memo:
(收稿日期:2020-02-19)国家自然科学基金资助项目(11532003,31670950)。△通信作者Email: dlh@cczu.edu.cn
更新日期/Last Update: 2020-10-16