Selection algorithm for parameters to characterize uterine EHG signals for the detection of preterm labor

This article proposes a selection method that can be applied to choose the best parameters to classify contractions in the uterine electrohysterography (EHG) signal for the detection of preterm labor. Several types of parameters have historically been extracted from the electrohysterogram. These can be divided into three classes: linear parameters, nonlinear parameters and parameters related to the electrohyterogram propagation. Frequency band enhancement EHG characterization has also been extensively studied. Our work is divided in two parts. The first part is to implement and compute all the parameters already extracted from the EHG that have been published in the literature. These parameters were computed both on the original EHG and on different frequency bands obtained using wavelet packet decomposition. In the second part, we will use a new parameters selection method to eliminate all parameters that are not efficient and pertinent for classification. Our results indicate a set of 13 linear parameters, 3 nonlinear parameters and 2 propagation parameters that are potentially most useful to discriminate between pregnancy and labor contractions, either on different frequency bands or directly on original EHG.