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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]) |
ISSN | 14248220 |
EISSN | 1424-8220 |
卷号 | 21期号:2页码:1-15 |
发表状态 | 已发表 |
DOI | 10.3390/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 |
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: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 |
引用统计 | 正在获取...
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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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