School of Control Science and Engineering, Shandong University, 17923 Jingshi Road, Jinan 250061, People's Republic of China.
Med Biol Eng Comput. 2013 May;51(5):581-91. doi: 10.1007/s11517-012-1028-z. Epub 2013 Jan 22.
Pattern synchronization (PS) can capture one aspect of the dynamic interactions between bivariate physiological systems. It can be tested by several entropy-based measures, e.g., cross sample entropy (X-SampEn), cross fuzzy entropy (X-FuzzyEn), multivariate multiscale entropy (MMSE), etc. A comprehensive comparison on their distinguishability is currently missing. Besides, they are highly dependent on several pre-defined parameters, the threshold value r in particular. Thus, their consistency also needs further elucidation. Based on the well-accepted assumption that a tight coupling necessarily leads to a high PS, we performed a couple of evaluations over several simulated coupled models in this study. All measures were compared to each other with respect to their consistency and distinguishability, which were quantified by two pre-defined criteria-degree of crossing (DoC) and degree of monotonicity (DoM). Results indicated that X-SampEn and X-FuzzyEn could only work well over coupled stochastic systems with meticulously selected r. It is thus not recommended to apply them to the intrinsic complex physiological systems. However, MMSE was suitable for both, indicating by relatively higher DoC and DoM values. Final analysis on the cardiorespiratory coupling validated our results.
模式同步（PS）可以捕捉到双变量生理系统之间动态相互作用的一个方面。它可以通过几种基于熵的测度来测试，例如交叉样本熵（X-SampEn）、交叉模糊熵（X-FuzzyEn）、多变量多尺度熵（MMSE）等。目前还缺乏对它们可区分性的全面比较。此外，它们高度依赖于几个预定义的参数，特别是阈值 r。因此，它们的一致性也需要进一步阐明。基于耦合必然导致高 PS 的公认假设，我们在本研究中对几个模拟耦合模型进行了一些评估。所有的测量都与其他的进行了一致性和可区分性的比较，通过两个预先定义的标准——交叉度（DoC）和单调性度（DoM）来量化。结果表明，X-SampEn 和 X-FuzzyEn 只能在精心选择 r 的耦合随机系统中很好地工作。因此，不建议将它们应用于内在复杂的生理系统。然而，MMSE 适合两者，表现为相对较高的 DoC 和 DoM 值。对心肺耦合的最终分析验证了我们的结果。
