Influence of Electrode Placement on Signal Quality for Ambulatory Pregnancy Monitoring

Noninvasive fetal health monitoring during pregnancy has become increasingly important in order to prevent complications, such as fetal hypoxia and preterm labor. With recent advances in signal processing technology using abdominal electrocardiogram (ECG) recordings, ambulatory fetal monitoring throughout pregnancy is now an important step closer to becoming feasible. The large number of electrodes required in current noise-robust solutions, however, leads to high power consumption and reduced patient comfort. In this paper, requirements for reliable fetal monitoring using a minimal number of electrodes are determined based on simulations and measurement results. To this end, a dipole-based model is proposed to simulate different electrode positions based on standard recordings. Results show a significant influence of bipolar lead orientation on maternal and fetal ECG measurement quality, as well as a significant influence of interelectrode distance for all signals of interest

Performance of a condensed electrode patch compared to a diffuse electrode array for transabdominal fetal heart rate and uterine contraction monitoring: a preliminary report

Objective: Intrapartum monitoring of the fetal heart rate (FHR), maternal heart rate (MHR) and uterine activity (UA) can be done noninvasively via adhesive electrodes on the parturient’s abdominal surface. This approach, requiring multiple electrodes placed at specific positions on the abdomen, performs at least as well as ultrasound and tocodynamometry-based monitoring. We tested whether a single adhesive electrode template (a “patch”), which would simplify use and obviate errors in electrode placement, would function as well as diffusely arrayed single electrodes. Methods: Seventeen healthy term parturients were monitored simultaneously with a diffuse electrode array and a condensed array patch, each connected to an identical electronic processor. Equivalence of the two electrode systems was determined by comparing their success rate, percent agreement and percent equivalence for FHR and MHR detection. UA monitoring was assessed by comparing the percent agreement and sensitivity of the systems. Results: The success rates of the multiple electrode array and the patch for FHR and MHR detection were above 96%. The reliability of the patch was statistically equivalent to the standard electrode array. The percent agreement for FHR was 94.7 ± 4.0% and for MHR was 92.8 ± 5.3%. These were not affected by maternal body mass index or whether it was early or late labor. The percent equivalence for both FHR and MHR was above 98% indicating equivalence of the patch with the diffuse electrode array in the accuracy of heart rate detection. The percent agreement of UA detection between the patch and the electrode array averaged 98% and was not influenced by whether it was early or late labor. The sensitivity of the patch for detecting individual contractions was 86.1%, equivalent to the standard electrode array. However, the sensitivity was lower in early compared to late labor (82.1 ± 13.9 vs. 90.3 ± 9.3%; P=0.052). The lower 95% confidence limit in early labor (74.9%) fell below the 80% limit necessary for equivalence. Conclusion: The performance of an electrode patch template for intrapartum monitoring of fetal and maternal heart rate and uterine contractions was equivalent to that of a more diffuse electrode array in almost all respects

Evaluation and patient experience of wireless noninvasive fetal heart rate monitoring devices

Introduction: In clinical practice, fetal heart rate monitoring is performed intermittently using Doppler ultrasound, typically for 30 minutes. In case of a non-reassuring heart rate pattern, monitoring is usually prolonged. Noninvasive fetal electrocardiography may be more suitable for prolonged monitoring due to improved patient comfort and signal quality. This study evaluates the performance and patient experience of four noninvasive electrocardiography devices to assess candidate devices for prolonged noninvasive fetal heart rate monitoring. Material and methods: Non-critically sick women with a singleton pregnancy from 24 weeks of gestation were eligible for inclusion. Fetal heart rate monitoring was performed during standard care with a Doppler ultrasound device (Philips Avalon-FM30) alone or with this Doppler ultrasound device simultaneously with one of four noninvasive electrocardiography devices (Nemo Fetal Monitoring System, Philips Avalon-Beltless, Demcon Dipha-16 and Dräger Infinity-M300). Performance was evaluated by: success rate, positive percent agreement, bias, 95% limits of agreement, regression line, root mean square error and visual agreement using FIGO guidelines. Patient experience was captured using a self-made questionnaire. Results: A total of 10 women were included per device. For fetal heart rate, Nemo performed best (success rate: 99.4%, positive percent agreement: 94.2%, root mean square error 5.1 BPM, bias: 0.5 BPM, 95% limits of agreement: −9.7 – 10.7 BPM, regression line: y = −0.1x + 11.1) and the cardiotocography tracings obtained simultaneously by Nemo and Avalon-FM30 received the same FIGO classification. Comparable results were found with the Avalon-Beltless from 36 weeks of gestation, whereas the Dipha-16 and Infinity-M300 performed significantly worse. The Avalon-Beltless, Nemo and Infinity-M300 closely matched the performance of the Avalon-FM30 for maternal heart rate, whereas the performance of the Dipha-16 deviated more. Patient experience scores were higher for the noninvasive electrocardiography devices. Conclusions: Both Nemo and Avalon-Beltless are suitable devices for (prolonged) noninvasive fetal heart rate monitoring, taking their intended use into account. But outside its intended use limit of 36 weeks’ gestation, the Avalon-Beltless performs less well, comparable to the Dipha-16 and Infinity-M300, making them currently unsuitable for (prolonged) noninvasive fetal heart rate monitoring. Noninvasive electrocardiography devices appear to be preferred due to greater comfort and mobility.</p

A non-invasive multimodal foetal ECG–Doppler dataset for antenatal cardiology research

Non-invasive foetal electrocardiography (fECG) continues to be an open topic for research. The development of standard algorithms for the extraction of the fECG from the maternal electrophysiological interference is limited by the lack of publicly available reference datasets that could be used to benchmark different algorithms while providing a ground truth for foetal heart activity when an invasive scalp lead is unavailable. In this work, we present the Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research (NInFEA), the first open-access multimodal early-pregnancy dataset in the field that features simultaneous non-invasive electrophysiological recordings and foetal pulsed-wave Doppler (PWD). The dataset is mainly conceived for researchers working on fECG signal processing algorithms. The dataset includes 60 entries from 39 pregnant women, between the 21st and 27th week of gestation. Each dataset entry comprises 27 electrophysiological channels (2048 Hz, 22 bits), a maternal respiration signal, synchronised foetal trans-abdominal PWD and clinical annotations provided by expert clinicians during signal acquisition. MATLAB snippets for data processing are also provided

Influence of Electrode Placement on Quality of Abdominal Fetal Electrocardiography

Tato diplomová práce se zabývá problematikou monitorace plodového elektrokardiogramu pomocí transabdominální fetální elektrokardiografie. Tato metoda má velký potenciál v budoucnu nahradit kardiotokografii, která je v současné době nejpoužívanější metodou v klinické praxi. Transabdominální monitorace plodu se potýká s velkým množstvím problémů, jedním ze zásadních problémů je neexistující standardizace pro rozložení elektrod. Cílem této práce je přispět k řešení problému s umístěním elektrod pomocí objektivních metod, které se v současné době využívají především pro konvenční EKG. Výsledný návrh pro umístění elektrod autorka vytvořila na základě vyhodnocení kvality signálů z dostupných databází pomocí objektivních parametrů v závislosti na úspěšnosti extrakce plodové složky z abdominálního signálu. Pro zvýšení přínosu této práce pro budoucí výzkum jsou dosažené výsledky evaluovány experty v oboru.This diploma thesis focuses on fetal monitoring recorded transabdominally. This method is very promising in replacing cardiotocography (CTG) which is the most used method in clinical practice. Transabdominal fetal monitoring faces a large number of problems, one of the major problems being the non-existent standardization for electrode placement. The aim of this work is to contribute to solving the problem with the placement of electrodes using objective methods, which are currently used mainly for conventional ECG. The author created the final design for the placement of electrodes based on the evaluation of the quality of signals from available databases using objective parameters depending on the success of the extraction of the fetal component from the abdominal signal. To increase the contribution of this work to future research, the results are evaluated by experts in the field.450 - Katedra kybernetiky a biomedicínského inženýrstvívýborn

Machine learning Ensemble Modelling to classify caesarean section and vaginal delivery types using cardiotocography traces

Human visual inspection of Cardiotocography traces is used to monitor the foetus during labour and avoid neonatal mortality and morbidity. The problem, however, is that visual interpretation of Cardiotocography traces is subject to high inter and intra observer variability. Incorrect decisions, caused by miss-interpretation, can lead to adverse perinatal outcomes and in severe cases death. This study presents a review of human Cardiotocography trace interpretation and argues that machine learning, used as a decision support system by obstetricians and midwives, may provide an objective measure alongside normal practices. This will help to increase predictive capacity and reduce negative outcomes. A robust methodology is presented for feature set engineering using an open database comprising 552 intrapartum recordings. State-of-the-art in signal processing techniques is applied to raw Cardiotocography foetal heart rate traces to extract 13 features. Those with low discriminative capacity are removed using Recursive Feature Elimination. The dataset is imbalanced with significant differences between the prior probabilities of both normal deliveries and those delivered by caesarean section. This issue is addressed by oversampling the training instances using a synthetic minority oversampling technique to provide a balanced class distribution. Several simple, yet powerful, machine-learning algorithms are trained, using the feature set, and their performance is evaluated with real test data. The results are encouraging using an ensemble classifier comprising Fishers Linear Discriminant Analysis, Random Forest and Support Vector Machine classifiers, with 87% (95% Confidence Interval: 86%, 88%) for Sensitivity, 90% (95% CI: 89%, 91%) for Specificity, and 96% (95% CI: 96%, 97%) for the Area Under the Curve, with a 9% (95% CI: 9%, 10%) Mean Square Error

Feasibility and analysis of bipolar concentric recording of Electrohysterogram with flexible active electrode

The conduction velocity and propagation patterns of Electrohysterogram (EHG) provide fundamental information about uterine electrophysiological condition. The accuracy of these measurements can be impaired by both the poor spatial selectivity and sensitivity to the relative direction of the contraction propagation associated with conventional disc electrodes. Concentric ring electrodes could overcome these limitations the aim of this study was to examine the feasibility of picking up surface EHG signals using a new flexible tripolar concentric ring electrode (TCRE), and to compare it with conventional bipolar recordings. Simultaneous recording of conventional bipolar signals and bipolar concentric EHG (BC-EHG) were carried out on 22 pregnant women. Signal bursts were characterized and compared. No significant differences among channels in either duration or dominant frequency in the Fast Wave High frequency range were found. Nonetheless, the high pass filtering effect of the BC-EHG records resulted in lower frequency content within the range 0.1 to 0.2 Hz than the bipolar ones. Although the BC-EHG signal amplitude was about 5-7 times smaller than that of bipolar recordings, similar signal-to-noise ratio was obtained. These results suggest that the flexible TCRE is able to pick up uterine electrical activity and could provide additional information for deducing uterine electrophysiological condition.The authors are grateful to the Obstetrics Unit of the Hospital Universitario La Fe de Valencia (Valencia, Spain), where the recording sessions were carried out. The work was supported in part by the Ministerio de Ciencia y Tecnologia de Espana (TEC2010-16945), by the Universitat Politecnica de Valencia (PAID SP20120490) and Generalitat Valenciana (GV/2014/029) and by General Electric Healthcare.Ye Lin, Y.; Alberola Rubio, J.; Prats Boluda, G.; Perales Marin, AJ.; Desantes, D.; Garcia Casado, FJ. (2015). 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Saade. Comparing uterine electromyography activity of antepartum patients vs. term labor patients. Am. J. Obstet. Gynecol. 193(1):23–29, 2005.Garfield, R. E., H. Maul, L. Shi, W. Maner, C. Fittkow, G. Olsen, and G. R. Saade. Methods and devices for the management of term and preterm labor. Ann. N. Y. Acad. Sci. 943(1):203–224, 2001.Hassan, M., J. Terrien, C. Muszynski, A. Alexandersson, C. Marque, and B. Karlsson. Better pregnancy monitoring using nonlinear correlation analysis of external uterine electromyography. IEEE Trans. Biomed. Eng. 60(4):1160–1166, 2013.Kaufer, M., L. Rasquinha, and P. Tarjan. Optimization of multi-ring sensing electrode set, Conference proceedings of IEEE Engineering in Medicine and Biology Society, 1990, pp. 612–613.Koka, K., and W. G. Besio. Improvement of spatial selectivity and decrease of mutual information of tri-polar concentric ring electrodes. J. Neurosci. Methods 165(2):216–222, 2007.Lu, C.-C., and P. P. Tarjan. 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Prediction of Labor Induction Success from the Uterine Electrohysterogram

[EN] Pharmacological agents are often used to induce labor. Failed inductions are associated with unnecessarily long waits and greater maternal-fetal risks, as well as higher costs. No reliable models are currently able to predict the induction outcome from common obstetric data (area under the ROC curve (AUC) between 0.6 and 0.7). The aim of this study was to design an early success-predictor system by extracting temporal, spectral, and complexity parameters from the uterine electromyogram (electrohysterogram (EHG)). Different types of feature sets were used to design and train artificial neural networks: Set_1: obstetrical features, Set_2: EHG features, and Set_3: EHG+obstetrical features. Predictor systems were built to classify three scenarios: (1) induced women who reached active phase of labor (APL) vs. women who did not achieve APL (non-APL), (2) APL and vaginal delivery vs. APL and cesarean section delivery, and (3) vaginal vs. cesarean delivery. For Scenario 3, we also proposed 2-step predictor systems consisting of the cascading predictor systems from Scenarios 1 and 2. EHG features outperformed traditional obstetrical features in all the scenarios. Little improvement was obtained by combining them (Set_3). The results show that the EHG can potentially be used to predict successful labor induction and outperforms the traditional obstetric features. Clinical use of this prediction system would help to improve maternal-fetal well-being and optimize hospital resources.This work received financial support from the Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund (DPI2015-68397-R and RTI2018-094449-A-I00), Universitat Politècnica de València VLC/Campus (UPV-FE-2018-B02), Generalitat Valenciana (GV/2018/104), and Bial S.A.Benalcazar-Parra, C.; Ye Lin, Y.; Garcia-Casado, J.; Monfort-Ortiz, R.; Alberola Rubio, J.; Perales Marin, AJ.; Prats-Boluda, G. (2019). 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