Janson N B, Balanov A G, Anishchenko V S, McClintock P V E
Department of Physics, Lancaster University, Lancaster, LA1 4YB, United Kingdom.
Phys Rev E Stat Nonlin Soft Matter Phys. 2002 Mar;65(3 Pt 2A):036212. doi: 10.1103/PhysRevE.65.036212. Epub 2002 Feb 15.
The recently proposed approach to detect synchronization from univariate data is applied to heart-rate-variability (HRV) data from ten healthy humans. The approach involves introducing angles for return times map and studying their behavior. For filtered human HRV data, it is demonstrated that: (i) in many of the subjects studied, interactions between different processes within the cardiovascular system can be considered as weak, and the angles can be well described by the derived model; (ii) in some of the subjects the strengths of the interactions between the processes are sufficiently large that the angles map has a distinctive structure, which is not captured by our model; (iii) synchronization between the processes involved can often be detected; (iv) the instantaneous radii are rather disordered.
最近提出的从单变量数据中检测同步性的方法被应用于来自十名健康人的心率变异性（HRV）数据。该方法包括为返回时间映射引入角度并研究其行为。对于经过滤波的人体HRV数据，结果表明：（i）在许多研究对象中，心血管系统内不同过程之间的相互作用可被视为较弱，并且角度可以通过推导模型得到很好的描述；（ii）在一些研究对象中，过程之间相互作用的强度足够大，以至于角度映射具有独特的结构，而我们的模型无法捕捉到这种结构；（iii）通常可以检测到所涉及过程之间的同步性；（iv）瞬时半径相当无序。
