  Estimation of the fetal heart rate (FHR) has gained interest in the last
century, low heart rate variability has been studied to identify intrauterine
growth restricted fetuses (prepartum), and abnormal FHR patterns have been
associated with fetal distress during delivery (intrapartum). Several
monitoring techniques have been proposed for FHR estimation, including
auscultation and Doppler ultrasound. This thesis focuses on the extraction of
the non-invasive fetal electrocardiogram (NI-FECG) recorded from a limited set
of abdominal sensors. The main challenge with NI-FECG extraction techniques is
the low signal-to-noise ratio of the FECG signal on the abdominal mixture
signal which consists of a dominant maternal ECG component, FECG and noise.
However the NI-FECG offers many advantages over the alternative fetal
monitoring techniques, the most important one being the opportunity to enable
morphological analysis of the FECG which is vital for determining whether an
observed FHR event is normal or pathological. In order to advance the field of
NI-FECG signal processing, the development of standardised public databases and
benchmarking of a number of published and novel algorithms was necessary.
