Singular Value Decomposition for Removal of Cardiac Interference from Trunk Electromyogram.
Singular Value Decomposition for Removal of Cardiac Interference from Trunk Electromyogram.
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DOI：
10.3390/s21020573
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发表时间：
2021-01-15
期刊：
影响因子：
--
通讯作者：
Mischi M
中科院分区：
文献类型：
--
作者：
Peri E;Xu L;Ciccarelli C;Vandenbussche NL;Xu H;Long X;Overeem S;van Dijk JP;Mischi M
提出了一种基于奇异值分解（SVD）的躯干肌电信号（EMG）心脏污染去除新算法。它的性能相比，目前可用的算法在不同的信号噪声比（SNR）。该算法适用于各个通道。提出了一种实验校准曲线，以调整SVD分量的数量的SNR（0-20 dB）。通过心电图（ECG）和EMG的组合生成合成数据集，以建立用于验证的地面真实参考。的性能进行了比较，与国家的最先进的算法：门控，高通滤波，模板减法（TS），和独立分量分析（伊卡）。它的适用性真实的数据进行了研究，在一个说明性的膈肌肌电图与睡眠呼吸暂停患者。基于SVD的算法在重建躯干肌电信号方面优于现有的方法。在时域（相对均方误差< 15%）和频域（平均频移<1Hz）上上级其它方法。在膈肌肌电图上证明了其可行性，与TS和伊卡相比，膈肌肌电图与呼吸周期的一致性更好（相关系数= 0.81，p值< 0.01）。它在真实的数据上的应用有望非侵入性地估计睡眠相关呼吸障碍的呼吸努力。该算法不限于需要额外的参考ECG，增加了其在临床实践中的适用性。
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.
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影响因子：
7.8
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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