Abstract:

Non-invasive fetal electrocardiography offers the potential to measure heart rate, heart ratevariability, and to analyse ECG waveform morphology of the fetal heart. It is a promisingtechnique for monitoring fetal cardiac activity using abdominal recordings. [1] Despite effortsto implement this technology in clinical practice, there remains no standardised electrodeplacement. The reasons for this shortcoming are that studies have faced the problem oflimited data sets and a lack of knowledge about the fetal electrocardiogram as it cannotbe sufficiently separated from the overlaying parental cardiac noise. [2] In this work, anapproach was developed to identify an optimal lead for a healthy fetus in a computationalmodel of a full pregnant female torso. This model offered the advantage of knowing thetrue fetal electrocardiogram without any noise. The signal strength was attributed to bean indicator of an appropriate electrode location. Therefore, several fitting features wereextracted for each node on the torso to create a feature map, representing the signal strengthdistribution. The features were based on the amplitudes and energy of the different segmentsof an electrocardiogram. To identify an optimal bipolar lead, an approach was developed todetect a lead on the parental torso that represented a lead on the fetal body, in this case LeadII, and was associated with a strong signal. Furthermore, a fetus in distress was modelled byadding myocardial ischaemia as well as a fetus in different positions to investigate the impacton the fetal signal. We observed that for the main mesh, the different features producedsimilar distributions. The energy of the full cycle served as a basis for identifying an optimalbipolar lead based on the fetal Lead II since it correlated the most with all other featuremaps. The Lead II representations originated from combinations of electrodes placed aroundthe abdomen and the back of the torso. The bipolar lead with the highest energy value hadan interelectrode distance of 183.2 mm and belonged to the leads that were close to themaximum of the feature map. An even higher energy value was associated with the leadwhose electrodes were placed at the two local maxima of the feature map, respectively. Sincethis lead was also similar to the Lead II on the fetal body with a correlation coefficient of0.9237, it was used to investigate the simulation results when the fetal heart suffered frommyocardial ischaemia. Here, the waveform changed considerably with respect to the healthycase. Further exploration of the feature maps showed that the signal strength distributionchanged for fetuses in different positions. In conclusion, we proposed a bipolar lead thatrepresented the fetal Lead II and acknowledged signal strength using a computational model.However, we also demonstrated that more studies are needed to identify an optimal set ofbipolar leads to cover the variety of common clinical scenarios.