In the fetal period, the progressive coordination among several subsystems promotes the emergence of sleep states. For this reason, the characterization of fetal behavioral states plays a crucial role in assessing fetal wellbeing. Nevertheless, current methodologies aimed at assessing fetal sleep states over limited time intervals require visual observation of the traces. In this work, we validate a point process approach for a continuous in time characterization of fetal behavioral states. We compare traditional heart rate variability (HRV) parameters and the corresponding point process-extracted sets of time and frequency measures in a population of 39 fetuses whose fetal ECG was recorded overnight during the third trimester of gestation.Clinical Relevance- Our results provide evidence for the proposed point process framework to capture fetal HRV dynamics with a high degree of reliability, suggesting its potential application for instantaneous estimates of fetal sleep states.