Categorization of heart rate-eye movement patterns in human fetuses using the statistical technique of discriminant...

The purpose of this study was to determine if discriminant analysis could be used to categorize fetal heart rate (FHR) - fetal eye movement (FEM) patterns. Statistical characteristics from 27 normal human fetuses at term for behavioral states, transitions, and insertions were established by combining the digitized FHR-FEM data for subjectively identical epochs. The mean FHR, the variance about the mean, and the presence or absence of FEM were calculated for each 3-min block in a sliding moving window with a 1-min step size. For each fetus, discriminant analysis was then used to assign 3-min blocks to either a behavioral state, a transition, or an insertion by comparing the statistical properties of a 3-min block with that of the data base. We found no difference between discriminant analysis and visual assignment in the average time spent in behavioral states 1F, 2F, and 4F, or in the mean duration of the transition/insertion periods. There was a highly significant linear relationship between computer-generated and visually-determined durations for behavioral states 1F (r = 0.972, p < 0.0001) and 2F (r = 0.989, p < 0.0001) and for the transition/insertion periods (r = 0.863, p < 0.0001). We conclude that discriminant analysis is a reliable computer-based method for behavioral state identification.