Data for: Integrating Machine Learning Techniques and Physiology Based Heart Rate Features for Antepartum Fetal Monitoring

The article contains a set of 12 linear and nonlinear indices extracted from Fetal Heart Rate (FHR) recordings by means of CTG monitors on two groups of fetuses: 60 normals and 60 Intra Uterine Growth Restricted (IUGR) fetuses. The two populations were selected by clinicians after birth on the basis of clinical standards for detecting growth restricted newborns (Apgar scores, percentile weight, …). The indices were computed on FHR recordings, each one lasting more than 30 minutes, by means of algorithms already published in the scientific literature.