Computational multivariate modeling of electrical activity of the porcine uterus during spontaneous and hormone-induced estrus

In pig production units, control of the estrous cycle and synchronization of ovulation have become routine herd management procedures. During the estrous cycle, under both induced and spontaneous conditions, the ovaries and the uterus undergo hormone-dominated physiological changes, these are consistent with the hypothesis that there is a functional role of uterine contractions in promoting fertilization. We have used electromyography to determine if the use of exogenous hormones, such as eCG and hCG, that have the potential to control the time of ovulation in female pigs, changes the multivariate relations between parameters of electrical bursts and modulates the patterns of myoelectrical activity. In the study presented here, we employed the mathematical approach of higher order multivariate cumulants in complex modeling of the myometrial electrical activity. The experiment was conducted on 12 mature Polish Landrace sows and uterine activity was recorded during both spontaneous and induced estrous cycles. The burst parameters were determined using six features, in the time domain and after the Fast Fourier transformation in the frequency domain. The evaluation of myoelectrical activity patterns was conducted based on the classical univariate statistical methods and the multivariate probabilistic modelling. The classical statistical approach indicated a weaker myoelectrical activity after hormonal stimulation, whereas the higher order multivariate statistical model showed evidence of similar status of activity and larger order of signals during induced estrus. Routine estrous cycle synchronization affects the multivariate probabilistic model of myometrial electrical activity.