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Monitoring procedures are the basis to evaluate the clinical state of patients and to assess changes in their conditions, thus
providing necessary interventions in time. Both these two objectives can be achieved by integrating technological developmentwith
methodological tools, thus allowing accurate classification and extraction of useful diagnostic information. The paper is focused
on monitoring procedures applied to fetal heart rate variability (FHRV) signals, collected during pregnancy, in order to assess fetal
well-being. The use of linear time and frequency techniques as well as the computation of non linear indices can contribute to
enhancing the diagnostic power and reliability of fetal monitoring.The paper shows how advanced signal processing approaches
can contribute to developing new diagnostic and classification indices. Their usefulness is evaluated by comparing two selected
populations: normal fetuses and intra uterine growth restricted (IUGR) fetuses. Results show that the computation of different
indices on FHRV signals, either linear and nonlinear, gives helpful indications to describe pathophysiological mechanisms involved
in the cardiovascular and neural system controlling the fetal heart. As a further contribution, the paper briefly describes how the
introduction of wearable systems for fetal ECG recording could provide new technological solutions improving the quality and
usability of prenatal monitoring
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