FETAL HEART RATE ANALYSIS BY HIERARCHICAL DIRICHLET PROCESS MIXTURE MODELS

In this paper, we propose to analyze fetal heart rate (FHR) signals by hierarchical Dirichlet process (HDP) mixture models. We investigate whether the clustering results of real-world FHR time series obtained by these models are informative in terms of determining the health status of a fetus. The FHR signals are divided into two groups, healthy and unhealthy, according to the umbilical arterial blood pH values of the fetuses. We computed the frequencies of clusters appearing in each of the groups, and applied the Mann-Whitney U test to compare the frequencies. The results showed that the frequencies of appearance of certain clusters are statistically significantly different across the two groups. This indicates that certain clusters may relate to pathological fetal heart rate patterns.