Oczeretko Edward, Swiatecka Jolanta, Kitlas Agnieszka, Laudanski Tadeusz, Pierzynski Piotr
Institute of Computer Science, University of Białystok, Sosnowa 64, 15-887 Bialystok, Poland.
Med Eng Phys. 2006 Jan;28(1):75-81. doi: 10.1016/j.medengphy.2005.03.011.
In physiological research, we often study multivariate data sets, containing two or more simultaneously recorded time series. The aim of this paper is to present the cross-correlation and the wavelet cross-correlation methods to assess synchronization between contractions in different topographic regions of the uterus. From a medical point of view, it is important to identify time delays between contractions, which may be of potential diagnostic significance in various pathologies. The cross-correlation was computed in a moving window with a width corresponding to approximately two or three contractions. As a result, the running cross-correlation function was obtained. The propagation% parameter assessed from this function allows quantitative description of synchronization in bivariate time series. In general, the uterine contraction signals are very complicated. Wavelet transforms provide insight into the structure of the time series at various frequencies (scales). To show the changes of the propagation% parameter along scales, a wavelet running cross-correlation was used. At first, the continuous wavelet transforms as the uterine contraction signals were received and afterwards, a running cross-correlation analysis was conducted for each pair of transformed time series. The findings show that running functions are very useful in the analysis of uterine contractions.
在生理学研究中，我们经常研究多变量数据集，其中包含两个或多个同时记录的时间序列。本文的目的是介绍互相关和小波互相关方法，以评估子宫不同地形区域收缩之间的同步性。从医学角度来看，识别收缩之间的时间延迟很重要，这在各种病理情况中可能具有潜在的诊断意义。互相关是在一个移动窗口中计算的，窗口宽度对应于大约两到三次收缩。结果，得到了运行互相关函数。从该函数评估的传播%参数允许对双变量时间序列中的同步性进行定量描述。一般来说，子宫收缩信号非常复杂。小波变换提供了对不同频率（尺度）下时间序列结构的洞察。为了显示传播%参数沿尺度的变化，使用了小波运行互相关。首先，接收作为子宫收缩信号的连续小波变换，然后对每对变换后的时间序列进行运行互相关分析。研究结果表明，运行函数在子宫收缩分析中非常有用。
