Abstract
There is a need for affordable, widely deployable maternal-fetal ECG monitors to improve maternal and fetal health during pregnancy and delivery. Based on the diffusion-based channel selection, here we present the mathematical formalism and clinical validation of an algorithm capable of accurate separation of maternal and fetal ECG from a two channel signal acquired over maternal abdomen. The proposed algorithm is the first algorithm, to the best of the authors' knowledge, focusing on the fetal ECG analysis based on two channel maternal abdominal ECG signal, and we apply it to two publicly available databases, the PhysioNet non-invasive fECG database (adfecgdb) and the 2013 PhysioNet/Computing in Cardiology Challenge (CinC2013), to validate the algorithm. The state-of-the-art results are achieved when compared with other available algorithms. Particularly, the F1 score for the R peak detection achieves 99.3% for the adfecgdb and 87.93% for the CinC2013, and the mean absolute error for the estimated R peak locations is 4.53 ms for the adfecgdb and 6.21 ms for the CinC2013. The method has the potential to be applied to other fetal cardiogenic signals, including cardiac doppler signals.
Highlights
Fetal electrocardiogram (ECG) and the fetal heart rate (HR) provide enormous information about fetal health
The same idea could be applied to other algorithms, like recursive least square (RLS), but to keep the discussion simple, we focus on the above-mentioned two typical algorithms, least mean square (LMS) and echo state neural network (ESN)
To the best of our knowledge, less is published about two aECG channels approach, and our proposed method focuses on this direction
Summary
Fetal electrocardiogram (ECG) and the fetal heart rate (HR) provide enormous information about fetal health. From clinical studies and animal models, evidence is accumulating that perinatal brain injury originates in utero, yet no means exist to detect its onset early, reliably and with simple, widely accessible means (Anblagan et al, 2016). A harbinger of brain injury is the fetal inflammatory response (Hagberg et al, 2015). There is an urgent need for early antenatal detection of fetal inflammatory response to prevent or at least mitigate the developing perinatal brain injury. We derived a set of fetal HR features that is specific to brain or gut inflammation (Liu et al, 2016). Such systemic and organspecific tracking of inflammation via fetal HR is possible due to the brain-innate immune system
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