Bray M A, Lin S F, Aliev R R, Roth B J, Wikswo J P
Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37235, USA.
J Cardiovasc Electrophysiol. 2001 Jun;12(6):716-22. doi: 10.1046/j.1540-8167.2001.00716.x.
Quantitative analysis of complex self-excitatory wave patterns, such as cardiac fibrillation and other high-order reentry, requires the development of new tools for identifying and tracking the most important features of the activation, such as phase singularities.
Image processing operations can be used to detect the phase singularity at the tip of a spiral wave. The phase space behavior of a spatiotemporal sequence of data may be reconstructed using time-series analysis. The phase singularities then are localized efficiently by computing the topologic charge density as the curl of the spatial phase gradient. We analyzed the singularity interaction dynamics of both experimentally observed and numerically simulated instances of quatrefoil reentry and found that the singularity behavior in the experimental preparations can be classified into three categories on the basis of how their separation changes with time.
Topologic charge densities can be calculated easily and efficiently to reveal phase singularity behavior. However, the differences between theoretical and experimental observations of singularity separation distances indicate the need for more sophisticated numerical models.
对复杂的自激波模式进行定量分析，如心脏颤动和其他高阶折返，需要开发新工具来识别和追踪激活的最重要特征，如相位奇点。
图像处理操作可用于检测螺旋波尖端的相位奇点。时空数据序列的相空间行为可使用时间序列分析进行重建。然后通过计算作为空间相位梯度旋度的拓扑电荷密度来有效地定位相位奇点。我们分析了实验观察和数值模拟的四叶形折返实例的奇点相互作用动力学，发现实验制剂中的奇点行为可根据其间距随时间的变化分为三类。
可以轻松有效地计算拓扑电荷密度以揭示相位奇点行为。然而，奇点间距的理论和实验观察之间的差异表明需要更复杂的数值模型。
