Fetal Heart Rate Features of Healthy and Late IUGR Fetuses

Citation Author(s):
Nicolò
Pini
Politecnico di Milano
Maristella
Lucchini
Columbia University Irving Medical Center
Giuseppina
Esposito
Federico II University
Marta
Campanile
Federico II University
Giovanni
Magenes
University of Pavia
Maria G.
Signorini
Politecnico di Milano
Submitted by:
NICOLO PINI
Last updated:
Tue, 03/24/2020 - 21:46
DOI:
10.21227/mzc6-jt52
Data Format:
License:
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Abstract 

The dataset consists of two populations of fetuses: 160 healthy and 102 Late Intra Uterine Growth Restricted (IUGR). Late IUGR is an adverse pathological condition encompassing chronic hypoxia as a consequence of placental insufficiency, resulting in an abnormal rate of fetal growth. In standard clinical practice, Late IUGR diagnosis can only be suspected in the third trimester and ultimately confirmed at birth. This data collection comprises of a set of 31 Fetal Heart Rate (FHR) indices computed at different time scales and domains accompanied by the clinical diagnosis. Antepartum CTG recordings were collected at the Azienda Ospedaliera Universitaria Federico II (Napoli, Italy), during daily routine monitoring. Traces were recorded in a controlled clinical environment, with participants lying supine and undergoing a standard non-stress test protocol using Philips Avalon FM30. The acquired traces are of duration equal to 40 minutes and sampled at 2 Hz.

Each CTG recording was subdivided in epochs of 120 samples (1-min) or 360 samples (3-min) prior to feature extraction. The choice of 1-min or 3-min subintervals is based upon to the different time scales on which FHR indices are computed. Regarding artifacts identification, we discarded segments including more than five consecutive samples or more than 5% of samples (6 FHR values out of 120 points per subinterval or 18 FHR values out of 360 points per subinterval) for which the FHR could not be detected. Lastly, isolated samples of insufficient quality were substituted by the moving average of the nearest five FHR points. The parameters obtained for all the segments of one recording are then averaged to derive a single value for each parameter for any given recording.

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