论文标题
来自多铅ECG数据的多重复发网络
Multiplex Recurrence Networks from multi-lead ECG data
论文作者
论文摘要
我们提出了一种使用多重复发网络（MRNS）的框架工作来分析多铅ECG数据的综合方法。我们探讨了他们的内层和层间拓扑特征如何捕获基础时空动力学的复发模式的细微变化。我们发现，来自健康病例的心电图数据中的MRN与高度相互信息和各个程度分布之间的差异更少相干。在疾病的情况下，可以看到层之间相似性的特定度量的显着差异。在与局部异常相关的疾病（例如束分支块）相关的疾病中，相干性受到最大影响。我们注意到，使用所有措施进行疾病特异性模式进行全面分析很重要。我们的方法非常笼统，因此可以在高度复杂系统获得多元或多渠道数据的任何其他领域中应用。
We present an integrated approach to analyse the multi-lead ECG data using the frame work of multiplex recurrence networks (MRNs). We explore how their intralayer and interlayer topological features can capture the subtle variations in the recurrence patterns of the underlying spatio-temporal dynamics. We find MRNs from ECG data of healthy cases are significantly more coherent with high mutual information and less divergence between respective degree distributions. In cases of diseases, significant differences in specific measures of similarity between layers are seen. The coherence is affected most in the cases of diseases associated with localized abnormality such as bundle branch block. We note that it is important to do a comprehensive analysis using all the measures to arrive at disease-specific patterns. Our approach is very general and as such can be applied in any other domain where multivariate or multi-channel data are available from highly complex systems.
