Noninvasive Imaging of Epicardial and Endocardial Potentials With Low Rank and Sparsity Constraints
Noninvasive Imaging of Epicardial and Endocardial Potentials With Low Rank and Sparsity Constraints
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DOI：
10.1109/tbme.2019.2894286
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发表时间：
2019-01
影响因子：
4.6
通讯作者：
Lin Fang;Jingjia Xu;Hongjie Hu;Yunmei Chen;P. Shi;Linwei Wang;Huafeng Liu
中科院分区：
文献类型：
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作者：
Lin Fang;Jingjia Xu;Hongjie Hu;Yunmei Chen;P. Shi;Linwei Wang;Huafeng Liu
在这项研究中，我们探讨了使用低秩和稀疏约束的体表心电图数据的心外膜和内膜细胞外电位的无创估计，以定位室性早搏（PVC）的焦点。该策略通过低秩稀疏分解来描述心电位的动态时空分布，其中低秩项表示平滑背景，异常电位在稀疏矩阵中提取。与大多数以前的基于势的方法相比，所提出的低秩和稀疏约束是批量时空约束，其捕获动态势的潜在关系。由此产生的优化问题求解使用交替方向法的乘数。对8个不同心室起搏部位的3组仿真实验表明，该模型在准确重构电位和定位心室起搏部位方面优于现有的Tikhonov正则化（零阶、二阶）和基于L1范数的方法.在39例真实的PVC数据上的实验也验证了所提出的方法正确定位异位起搏部位的能力。
In this study, we explore the use of low rank and sparse constraints for the noninvasive estimation of epicardial and endocardial extracellular potentials from body-surface electrocardiographic data to locate the focus of premature ventricular contractions (PVCs). The proposed strategy formulates the dynamic spatiotemporal distribution of cardiac potentials by means of low rank and sparse decomposition, where the low rank term represents the smooth background and the anomalous potentials are extracted in the sparse matrix. Compared to the most previous potential-based approaches, the proposed low rank and sparse constraints are batch spatiotemporal constraints that capture the underlying relationship of dynamic potentials. The resulting optimization problem is solved using alternating direction method of multipliers. Three sets of simulation experiments with eight different ventricular pacing sites demonstrate that the proposed model outperforms the existing Tikhonov regularization (zero-order, second-order) and L1-norm based method at accurately reconstructing the potentials and locating the ventricular pacing sites. Experiments on a total of 39 cases of real PVC data also validate the ability of the proposed method to correctly locate ectopic pacing sites.