In the era of digital twin technology (DTT), which involves creating virtual replicas of physical systems, healthcare applications have seen a surge in innovation. Fetal heart rate monitoring, a rapidly advancing field within healthcare, is benefiting greatly from the effective implementation of DTTs. Digital twin, supported by Artificial Intelligence (AI), Virtual Reality (VR), and Extended Virtuality (EV), have already demonstrated significant impact in entertainment, gaming, and media sectors. This paper explores and analyzes fetal heart rate monitoring systems during labor using digital twin technologies. During labor, there is an elevated risk of developing non-communicable diseases (NCDs) such as diabetes, cardiovascular diseases, cancer, and chronic respiratory diseases. The developmental origins of health and disease hypothesis posits that environmental conditions during fetal and early postnatal development have enduring effects on growth, structure, and metabolism, ultimately influencing long-term health and well-being. Understanding and effectively monitoring fetal heart rate dynamics during labor using digital twin technologies can provide valuable insights into maternal and fetal health. The findings underscore the value of entropy analysis in FHRV assessment, presenting a pioneering predictor of fetal health via ECG data. Moreover, it reveals the current landscape of fetal heart rate monitoring, discusses the integration of digital twins, and proposes future directions for optimizing healthcare outcomes in the digital era.