[1]孙文慧,张乙鹏,林冬梅,等.基于变分模态分解的肺音去噪算法[J].中国医学物理学杂志,2024,41(4):479-485.[doi:DOI:10.3969/j.issn.1005-202X.2024.04.013]
　SUN Wenhui,ZHANG Yipeng,et al.Lung sound denoising algorithm based on variational mode decomposition[J].Chinese Journal of Medical Physics,2024,41(4):479-485.[doi:DOI:10.3969/j.issn.1005-202X.2024.04.013]
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基于变分模态分解的肺音去噪算法()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
41卷
期数:
2024年第4期
页码:
479-485
栏目:
医学信号处理与医学仪器
出版日期:
2024-04-25

文章信息/Info

Title:
Lung sound denoising algorithm based on variational mode decomposition
文章编号:
1005-202X（2024）04-0479-07
作者:
孙文慧1; 2; 张乙鹏1; 2; 林冬梅3; 陈扶明2
1.甘肃中医药大学信息工程学院， 甘肃 兰州 730000； 2.中国人民解放军联勤保障部队第940医院医疗保障中心， 甘肃 兰州 730050； 3.兰州理工大学电气与信息工程学院， 甘肃 兰州 730050
Author(s):
SUN Wenhui1;  2;  ZHANG Yipeng1;  2;  LIN Dongmei3;  CHEN Fuming2
1. School of Information Engineering, Gansu University of Chinese Medicine, Lanzhou 730000, China 2. Medical Security Center, the 940th Hospital of Joint Logistics Support Force of Chinese Peoples Liberation Army, Lanzhou 730050, China 3. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
关键词:
肺音去噪; 变分模态分解; 经验模态分解
Keywords:
Keywords: lung sound denoising variational mode decomposition empirical mode decomposition
分类号:
R318；TP912.35
DOI:
DOI:10.3969/j.issn.1005-202X.2024.04.013
文献标志码:
A
摘要:
目的：为有效提高肺音信号质量，提出一种基于变分模态分解的肺音去噪方法。方法：首先利用经验模态分解对带噪肺音信号进行分解，根据本征模态函数特征确定最佳分解层数，然后根据分解层数对原始带噪肺音进行变分模态分解处理，接着根据皮尔逊系数选取有用模态，最后采用阈值方法对各模态函数去噪，重构后得到没有噪声干扰的肺音信号。结果：通过与维纳滤波和FIR滤波进行对比，本文方法的语音质量感知评价、短时间客观可读性和源信号失真比均更优。结论：本文方法能有效对肺音信号进行去噪处理。
Abstract:
Abstract: Objective To propose a lung sound denoising method based on variational mode decomposition (VMD) for effectively improving the quality of lung sound signals. Methods Empirical mode decomposition was utilized to decompose the noisy lung sound signal, and the optimal decomposition level was determined based on the intrinsic mode function features. Subsequently, the original noisy lung sound was processed with VMD according to the decomposition level, and the useful modes were then selected based on Pearson correlation coefficient. Finally, a threshold method was applied to the denoising of each mode function, and the lung sound signal without noise interference was obtained after reconstruction. Results Compared with Wiener filtering and finite impulse response filtering, the proposed method exhibited superior performance in perceptual evaluation of speech quality, short-time objective intelligibility, and signal-to-distortion ratio. Conclusion The proposed method can effectively remove the noise from lung sound signals.

相似文献/References:

[1]赵丽,崔立杰.基于变分模态分解的眼电伪迹去除[J].中国医学物理学杂志,2020,37(2):237.[doi:DOI:10.3969/j.issn.1005-202X.2020.02.018]
　ZHAO Li,CUI Lijie.Electrooculogram artifacts removal based on variational mode decomposition[J].Chinese Journal of Medical Physics,2020,37(4):237.[doi:DOI:10.3969/j.issn.1005-202X.2020.02.018]
[2]郁伟,李正权,邢松.改进WOA-VMD算法的心电信号去噪[J].中国医学物理学杂志,2023,40(9):1143.[doi:DOI:10.3969/j.issn.1005-202X.2023.09.014]
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备注/Memo

备注/Memo:
【收稿日期】2023-11-12 【基金项目】国家自然科学基金（61901515，62361038）；甘肃省自然科学基金（22JR5RA002） 【作者简介】孙文慧，硕士，研究方向：医学信号检测与处理，E-mail:877114569@qq.com 【通信作者】陈扶明，博士，高级工程师，研究方向：医学信号检测与处理，E-mail: cfm5762@126.com
更新日期/Last Update: 2024-04-25