Fetal Pulsed-Wave Doppler Atrioventricular Activity Detection by Envelope Extraction and Processing

Pulsed-Wave Doppler (PWD) is a diagnostic ultrasound technique widely used for fetal heart rate monitoring. Fetal PWD is particularly challenging since, beyond being intrinsically operator-dependent, different issues related to the fetal heart size, the fetal movements and the ultrasound artifacts appear. In long PWD recordings, the signal segments completely meaningful for a morphological analysis, i.e. including a readable atrial and ventricular activity, are then limited in number and duration. In this work, an approach for the automatic detection of the meaningful fetal cardiac activity from PWD video recordings is presented and evaluated, using the annotations made by an expert cardiologist. It consists of the video pre-processing for image thresholding, filtering and envelope extraction by edge detection, and a supervised classification stage. A dataset including 30 signals from 17 pregnant women was adopted, extracting from it multiple segments, including different quality recordings. A supervised classification approach for the detection of the signal segments completely meaningful for a morphological analysis was then applied, revealing an accuracy greater than 99%.