A Novel Noise Suppression and Artifact Removal Method of Mechanomyography Based on RLS, IGWO-VMD, and CEEMDAN

doi:10.1155/2022/4239211

	A Novel Noise Suppression and Artifact Removal Method of Mechanomyography Based on RLS, IGWO-VMD, and CEEMDAN
	Li, Zebin 1,2,3; Gao, Lifu 1,2; Lu, Wei 1,2; Wang, Daqing 1; Cao, Huibin 1; Zhang, Gang 3
刊名	JOURNAL OF SENSORS
	2022-09-06
卷号	2022
ISSN号	1687-725X
DOI	10.1155/2022/4239211
通讯作者	Li, Zebin(14000005@wxc.edu.cn) ; Gao, Lifu(lifugao@iim.ac.cn)
英文摘要	Mechanomyography (MMG) signals have extensive applications in muscle function assessment and human intention recognition. However, during signal acquisition, MMG signals are easily contaminated by noise and artifacts, which seriously affects the recognition of their characteristics. To address these issues, a novel noise suppression and artifact removal method based on recursive least square (RLS), improved Gray Wolf Optimizer-optimized variable mode decomposition (IGWO-VMD), and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is proposed. In this paper, the RLS algorithm is first applied to adaptively filter out the power line interference (PLI). Then, IGWO is designed to select the appropriate VMD parameters and use the VMD to decompose the noisy signal into band-limited intrinsic mode functions (BLIMFs). In addition, the BLIMFs are classified into the low-frequency part and high-frequency part according to the given correlation coefficient (CC) threshold value. The effective components of the low-frequency part are identified by the center frequency. Meanwhile, the high-frequency part is decomposed by CEEMDAN, and its effective components are obtained according to the proposed sample entropy threshold range. Finally, the effective components of the low and high-frequency parts are reconstructed to obtain the denoised signal to realize the extraction of useful signals. Simulation experiment results demonstrate that the proposed method outperforms the classical methods and the designed IGWO-VMD method in terms of denoising performance. The effectiveness of the proposed method is verified through the measured MMG signal experiments. The proposed method not only effectively suppresses noise and artifacts but also overcomes the limitations of VMD and CCEMDAN.
资助项目	National Natural Science Foundation of China ; Key Scientific Research Projects of Anhui Province Higher Education ; Strategic Priority Research Program of the Chinese Academy of Sciences ; University Synergy Innovation Program of Anhui Province ; HFIPS Director's Fund ; [92067205] ; [KJ2020A0630] ; [XDA22040303] ; [GXXT-2021-026] ; [YZJJ2021QN25]
WOS关键词	EMPIRICAL MODE DECOMPOSITION ; OPTIMIZATION ALGORITHM ; EMD ; SIGNALS
WOS研究方向	Engineering ; Instruments & Instrumentation
语种	英语
出版者	HINDAWI LTD
WOS记录号	WOS:000860924500006
资助机构	National Natural Science Foundation of China ; Key Scientific Research Projects of Anhui Province Higher Education ; Strategic Priority Research Program of the Chinese Academy of Sciences ; University Synergy Innovation Program of Anhui Province ; HFIPS Director's Fund
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/129187]
专题	中国科学院合肥物质科学研究院
通讯作者	Li, Zebin; Gao, Lifu
作者单位	1.Chinese Acad Sci, Inst Intelligent Machines, Hefei Inst Phys Sci, Hefei 230031, Peoples R China 2.Univ Sci & Technol China, Dept Sci Isl, Hefei 230026, Peoples R China 3.West Anhui Univ, Sch Elect & Photoelect Engn, Luan 237012, Peoples R China
推荐引用方式 GB/T 7714	Li, Zebin,Gao, Lifu,Lu, Wei,et al. A Novel Noise Suppression and Artifact Removal Method of Mechanomyography Based on RLS, IGWO-VMD, and CEEMDAN[J]. JOURNAL OF SENSORS,2022,2022.
APA	Li, Zebin,Gao, Lifu,Lu, Wei,Wang, Daqing,Cao, Huibin,&Zhang, Gang.(2022).A Novel Noise Suppression and Artifact Removal Method of Mechanomyography Based on RLS, IGWO-VMD, and CEEMDAN.JOURNAL OF SENSORS,2022.
MLA	Li, Zebin,et al."A Novel Noise Suppression and Artifact Removal Method of Mechanomyography Based on RLS, IGWO-VMD, and CEEMDAN".JOURNAL OF SENSORS 2022(2022).