Singular Value Decomposition for Removal of Cardiac Interference from Trunk Electromyogram
2021-01
发表期刊SENSORS (IF:3.4[JCR-2023],3.7[5-Year])
ISSN14248220
EISSN1424-8220
卷号21期号:2页码:1-15
发表状态已发表
DOI10.3390/s21020573
摘要

A new algorithm based on singular value decomposition (SVD) to remove cardiac contamination from trunk electromyography (EMG) is proposed. Its performance is compared to currently available algorithms at different signal-to-noise ratios (SNRs). The algorithm is applied on individual channels. An experimental calibration curve to adjust the number of SVD components to the SNR (0-20 dB) is proposed. A synthetic dataset is generated by the combination of electrocardiography (ECG) and EMG to establish a ground truth reference for validation. The performance is compared with state-of-the-art algorithms: gating, high-pass filtering, template subtraction (TS), and independent component analysis (ICA). Its applicability on real data is investigated in an illustrative diaphragm EMG of a patient with sleep apnea. The SVD-based algorithm outperforms existing methods in reconstructing trunk EMG. It is superior to the others in the time (relative mean squared error < 15%) and frequency (shift in mean frequency < 1 Hz) domains. Its feasibility is proven on diaphragm EMG, which shows a better agreement with the respiratory cycle (correlation coefficient = 0.81, p-value < 0.01) compared with TS and ICA. Its application on real data is promising to non-obtrusively estimate respiratory effort for sleep-related breathing disorders. The algorithm is not limited to the need for additional reference ECG, increasing its applicability in clinical practice.

关键词singular value decomposition trunk electromyography quantitative assessment of performance electrocardiograph interference respiratory monitoring
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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:000611709000001
出版者MDPI
EI入藏号20210409810603
EI主题词Singular value decomposition
EI分类号461.3 Biomechanics, Bionics and Biomimetics ; 461.6 Medicine and Pharmacology ; 703.2 Electric Filters ; 716.1 Information Theory and Signal Processing ; 921 Mathematics ; 922.2 Mathematical Statistics
原始文献类型Article
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文献类型期刊论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/125937
专题信息科学与技术学院_PI研究组_徐林组
通讯作者Peri, Elisabetta
作者单位
1.Eindhoven Univ Technol, Dept Elect Engn, NL-5600 MB Eindhoven, Netherlands;
2.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China;
3.Kempenhaeghe, Ctr Sleep Med, POB 61, NL-5590 AB Heeze, Netherlands;
4.Univ Ulm, Dept Orthodont, D-89081 Ulm, Germany
推荐引用方式
GB/T 7714
Peri, Elisabetta,Xu, Lin,Ciccarelli, Christian,et al. Singular Value Decomposition for Removal of Cardiac Interference from Trunk Electromyogram[J]. SENSORS,2021,21(2):1-15.
APA Peri, Elisabetta.,Xu, Lin.,Ciccarelli, Christian.,Vandenbussche, Nele L..,Xu, Hongji.,...&Mischi, Massimo.(2021).Singular Value Decomposition for Removal of Cardiac Interference from Trunk Electromyogram.SENSORS,21(2),1-15.
MLA Peri, Elisabetta,et al."Singular Value Decomposition for Removal of Cardiac Interference from Trunk Electromyogram".SENSORS 21.2(2021):1-15.
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