Use of piecewise stationary segmentation as a pre-treatment for synchronization measures

Effect of filtering on the classification rate of nonlinear analysis methods applied to uterine EMG signals

Nonlinear time series analysis can provide useful information regarding nonlinear features of biological signals. The effect of filtering on the performance of nonlinear methods is not well-understood. In this work, we investigate the effects of signal filtering on the sensitivity of four nonlinear methods: Time reversibility, Sample Entropy, Lyapunov Exponents and Delay Vector Variance. These methods were applied to uterine EMG signals with the aim of using them to discriminate between pregnancy and labor contractions. The signals were filtered using three different band-pass filters before the application of the methods. Results showed that the sensitivity of some methods such as sample entropy was significantly improved with filtering. On the other hand, filtering had little effect on some other methods such as time reversibility. This study concludes that while filtering increases computation time, it may be necessary for some nonlinear methods particularly those with low sensitivity.

Evolution of phase synchronization of the two frequency components of the electrohysterogram (EHG): application to the detection of human labor

The analysis of the electrical activity of the uterus recorded externally, the electrohysterogram (EHG), may find an application in the prediction of labor. In the literature parameters that are supposed to be related to the excitability of the uterine cells have almost exclusively been used for this purpose. In the present paper we evaluate the possible use of synchronization parameters for EHG measured in several places on the uterus for this prediction. The EHG is mainly composed of two frequency components called FWL and FWH. These components may be related to the synchronization and the excitability phenomenon respectively. In order to study independently these frequency components, we extracted the corresponding ridges of the wavelet transform of the EHG using the GVF-snake method. For each frequency component we computed parameters that are related to the frequency content of the signals and parameters that consider the synchronization relationship between signals. The synchronization parameters used were the mean phase coherence and the phase entropy. The values of the different parameters were compared during pregnancy and labor by statistical analysis. The detection quality of each parameter was evaluated using ROC curves. Our results suggest that synchronization parameters could be used for the detection of labor in addition to the classical previously published parameters. Another important result of our study is that both FWH and FWL seem related to excitability but only FWL seems to be related to the synchronization of the uterus at term.

Spatial analysis of uterine EMG signals: evidence of increased in synchronization with term

Evaluation of synchronization between signals can give new insights into the functioning of the related systems. Methods that can detect synchronization or coupling between signals can be divided two types: linear and non linear methods. In this paper we use the non linear correlation coefficient (h(2)) to show the difference in synchronization between efficient uterine contractions during labor and normal physiological contractions during pregnancy, in uterine activity bursts recorded at different places on the pregnant abdomen. Our interest in the non linear correlation coefficient is based on the fact that the propagation mechanism of uterine EMG signal may be strongly non linear. The results obtained from estimating the synchronization between 16 uterine EMG channels indicate that synchronization between contractions as measured by h(2) is stronger in labor than in pregnancy. Limited data indicates that the h(2) value increases markedly with term when expressed in duration before spontaneous labor.

Nonlinearity testing in the case of non Gaussian surrogates, applied to improving analysis of synchronicity in uterine contraction

Surrogates are commonly used to test a particular hypothesis on time series. The parameter commonly used in the literature to test these hypotheses is the z score. The z score assumes that the distribution of the statistics obtained on the surrogates is Gaussian. In this paper, we propose the use of a more general parameter than the z score that will also work in the case of non-Gaussian distribution of the statistics. We also derive a statistical test, based on the fitting of the distribution of the surrogate measure profile, in order to test the initial hypothesis. We validate the proposed approach on both synthetic signals and real uterine EMG signals by using the nonlinear correlation coefficient as initial statistic. We further show that this corrected nonlinear correlation coefficient can discriminate between pregnancy contractions and labor in a monkey, but the uncorrected nonlinear correlation coefficient cannot. This makes the corrected nonlinear correlation coefficient a promising candidate in a future application for preterm labor prediction in humans.