Non-Invasive Locating Of Premature Ventricular Contraction Origin With Low Rank/Tv Regularization

Lin Fang, Huafeng Liu
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Abstract

Most of the calculation methods for the electrocardiograph (ECG) inverse problem are based on priori assumptions of the instantaneous characteristics of the cardiac electrophysiology. In this paper, we have proposed a novel algorithm based on low rank and sparse decomposition (LSD) + total variation (TV) to solve the illposedness of dynamic ECG-inverse problem. The TV constraint filters out the disturbance of the noise and maintains the local smoothness of the potential. The LSD separates the sparse details from the potential background to prevent the potential details from being lost under the effect of smoothing constraint, thereby improving the accuracy of cardiac potential recovery.
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低秩/Tv正则化无创定位室性早搏起源
大多数心电图反问题的计算方法都是基于对心脏电生理瞬时特征的先验假设。本文提出了一种基于低秩稀疏分解(LSD) +总变分(TV)的新算法来解决动态心电图逆问题的病态性。电视约束滤除了噪声的干扰,保持了电势的局部平滑。LSD将稀疏细节从电位背景中分离出来,防止在平滑约束的作用下丢失电位细节,从而提高心电位恢复的准确性。
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