Comparative Review of the Algorithms for Removal of Electrocardiographic Interference from Trunk Electromyography

doi:10.3390/s20174890

	Comparative Review of the Algorithms for Removal of Electrocardiographic Interference from Trunk Electromyography
	Xu, Lin1 ; Peri, Elisabetta 2; Vullings, Rik 2; Rabotti, Chiara 3; Van Dijk, Johannes P.2,4; Mischi, Massimo 2
	2020-09
发表期刊	SENSORS (IF:3.4[JCR-2023],3.7[5-Year])
ISSN	1424-8220
卷号	20 期号:17 页码:4890
发表状态	已发表
DOI	10.3390/s20174890
摘要	Surface electromyogram (EMG) is a noninvasive measure of muscle electrical activity and has been widely used in a variety of applications. When recorded from the trunk, surface EMG can be contaminated by the cardiac electrical activity, i.e., the electrocardiogram (ECG). ECG may distort the desired EMG signal, complicating the extraction of reliable information from the trunk EMG. Several methods are available for ECG removal from the trunk EMG, but a comparative assessment of the performance of these methods is lacking, limiting the possibility of selecting a suitable method for specific applications. The aim of the present study is therefore to review and compare the performance of different ECG removal methods from the trunk EMG. To this end, a synthetic dataset was generated by combining in vivo EMG signals recorded on the biceps brachii and healthy or dysrhythmia ECG data from the Physionet database with a predefined signal-to-noise ratio. Gating, high-pass filtering, template subtraction, wavelet transform, adaptive filtering, and blind source separation were implemented for ECG removal. A robust measure of Kurtosis, i.e.,KR2and two EMG features, the average rectified value (ARV), and mean frequency (MF), were then calculated from the processed EMG signals and compared with the EMG before mixing. Our results indicate template subtraction to produce the lowest root mean square error in both ARV and MF, providing useful insight for the selection of a suitable ECG removal method.
关键词	trunk electromyography electrocardiography interference template subtraction adaptive filter wavelet blind source separation
URL	查看原文
收录类别	SCI ; SCIE ; EI
语种	英语
WOS研究方向	Chemistry ; Engineering ; Instruments & Instrumentation
WOS类目	Chemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS记录号	WOS:000571640800001
出版者	MDPI
EI入藏号	20203509116804
EI主题词	Adaptive filtering ; Adaptive filters ; Blind source separation ; Electrocardiography ; High pass filters ; Mean square error ; Signal to noise ratio ; Wavelet transforms
EI分类号	Medicine and Pharmacology:461.6 ; Electric Filters:703.2 ; Information Theory and Signal Processing:716.1 ; Mathematical Transformations:921.3 ; Mathematical Statistics:922.2
原始文献类型	Journal article (JA)
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/123605
专题	信息科学与技术学院_PI研究组_徐林组
通讯作者	Xu, Lin
作者单位	1.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China; 2.Eindhoven Univ Technol, Dept Elect Engn, NL-5600 MB Eindhoven, Netherlands; 3.Philips Res, NL-5656 AE Eindhoven, Netherlands; 4.Clin Phys Dept Kempenhaeghe, NL-6532 SZ Nijmegen, Netherlands
第一作者单位	信息科学与技术学院
通讯作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Xu, Lin,Peri, Elisabetta,Vullings, Rik,et al. Comparative Review of the Algorithms for Removal of Electrocardiographic Interference from Trunk Electromyography[J]. SENSORS,2020,20(17):4890.
APA	Xu, Lin,Peri, Elisabetta,Vullings, Rik,Rabotti, Chiara,Van Dijk, Johannes P.,&Mischi, Massimo.(2020).Comparative Review of the Algorithms for Removal of Electrocardiographic Interference from Trunk Electromyography.SENSORS,20(17),4890.
MLA	Xu, Lin,et al."Comparative Review of the Algorithms for Removal of Electrocardiographic Interference from Trunk Electromyography".SENSORS 20.17(2020):4890.