By studying the electrohysterogram (EHG) signals, which reveal the changes of the electric potentials of the uterus, we can tackle the problem of preterm birth prediction non-invasively. The aim is to separate the sets of preterm and term delivery EHG records based on the estimation of the velocity and direction of the electric potential propagation. We calculate the directions and velocities using the short-time cross-correlation procedure. We compare the values of pairs of parallel signals above and below, and left and right from the navel, and determine the time delays of the pairs of signals. Sequences of velocities and directions of travel of the propagation waves are calculated next. We defined features that describe the direction and velocity of propagation, and their regularity, and added some features that describe original signals. The features allow us to better understand the electrical activities of the uterus. We perform separation of the groups of records inside the selected frequency bands, and study the impact of different physiological mechanisms. In the frequency band below 1.0 Hz, the most influent on the electrical activity are the uterine contractions, while above 1.0 Hz, exclusively mother's heart beating. We analyse the records as whole, and characterize the selected individual intervals of records, i.e., intervals containing contractions, or non-contraction intervals. Besides the type of the intervals and the selected frequency band, we estimate also the classification accuracy of the defined features with regard to the time of recording. We conclude that studying the influence of the maternal heart
is of key importance during separating the groups of records since the highest classification accuracies were obtained above 1.0 Hz. The maternal heart influences are the most contributive when classifying non-contractions intervals. The highest classification results were obtained using those features that describe regularity of the original signals, and frequency of propagation of the electric potentials in horizontal direction. The last feature appeared to be the most important feature
when separating records recorded early during pregnancy, thus allowing early prediction of preterm birth in clinical practice.
|