title: Monitoring fetal heart rate during pregnancy: contributions from advanced signal processing and wearable technology.
abstract: 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 development with 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.
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milano, Italy.
authors.forename: Maria G
authors.initials: MG
authors.lastname: Signorini
authors.affiliation: Computational Physiological and Clinical Inference Group, 143 3rd Street, Apt. 1, Cambridge, MA 02141, USA.
authors.forename: Andrea
authors.identifier: 0000-0001-9876-9050
authors.initials: A
authors.lastname: Fanelli
authors.affiliation: Dipartimento di Ingegneria Industriale e dell'Informazione, University of Pavia, Via A. Ferrata 1, 27100 Pavia, Italy.
authors.forename: Giovanni
authors.identifier: 0000-0002-7558-1490
authors.initials: G
authors.lastname: Magenes
mesh_terms: D000465:Algorithms; D004562:Electrocardiography / Q000379:methods; D005260:Female; D005317:Fetal Growth Retardation / Q000175:diagnosis* / Q000473:pathology*; D005323:Fetal Monitoring / Q000379:methods*; D006321:Heart / Q000196:embryology; D006340:Heart Rate, Fetal; D006801:Humans; D008490:Medical Informatics / Q000379:methods; D017711:Nonlinear Dynamics; D011247:Pregnancy; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D018608:Ultrasonography, Doppler / Q000379:methods