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Background: In an Australian randomized controlled trial (RCT), two techniques for intrapartum fetal surveillance were compared: ST analysis (STan) as an adjunct to cardiotocography (CTG), compared with CTG alone. The aim was to determine whether CTG + STan could reduce emergency cesarean birth rates while maintaining or improving neonatal outcomes. Secondary aims were to compare clinical, economic, and psychosocial outcomes. The purpose of this paper was to present psychosocial outcomes from one cohort enrolled in the trial., Methods: The study was conducted at one tertiary referral hospital. Participants who had taken part in the trial from the outset were invited to complete a questionnaire between March 2018 and January 2020, approximately 8 weeks after giving birth. Outcomes included depression, psychological distress, health-related quality of life, and infant feeding practices. Analysis was by intention to treat., Results: N = 207/527 participants completed the questionnaire (n = 113, STan; n = 94, CTG alone). Overall, no statistically significant or clinically meaningful differences were found in the two groups for symptoms of depression, psychological distress, quality of life, or infant feeding. A statistically significant difference was observed for the subscale of pain-discomfort, where scores were higher on average in the CTG alone arm relative to that in the CTG + STan arm., Conclusions: Although STan as an adjunct to CTG constitutes a different clinical technology from CTG alone, both monitoring types appeared to produce similar results in terms of postnatal psychosocial outcomes for women. Findings from this study provide service users and staff with a comprehensive assessment of STan that can be used to make evidence-informed decisions about monitoring options should STan become more widely available., (© 2024 The Authors. Birth published by Wiley Periodicals LLC.)

Intrapartum care uses electronic fetal heart rate monitoring (EFHRM) for over 50 years to indirectly assess fetal oxygenation. However, this approach has been associated with an increase in cesarean delivery rates and limited improvements in neonatal hypoxic outcome. To address these shortcomings, a novel transabdominal fetal pulse oximeter (TFO) is being developed to provide an objective measurement of fetal oxygenation. Previous studies have evaluated the performance of TFO on pregnant ewe. Building on the animal model, this study aims to determine whether TFO can successfully capture human fetal heart rate (FHR) signals during non-stress testing (NST) as a proof-of-concept. Eight ongoing pregnancies meeting specific inclusion criteria (18-40 years old, singleton, and at least 36 weeks' gestation) were enrolled with consent. Each study session was 15 to 20 min long. Reference maternal heart rate (MHR) and FHR were obtained using finger pulse oximetry and cardiotocography for subsequent comparison. The overall root-mean-square error was 9.7BPM for FHR and 4.4 for MHR, while the overall mean-absolute error was 7.6BPM for FHR and 1.8 for MHR. Bland-Altman analysis displayed a mean bias ± standard deviation between TFO and reference of -3.9 ± 8.9BPM, with limits of agreement ranging from -21.4 to 13.6 BPM. Both maternal and fetal heart rate measurements obtained from TFO exhibited a p-value < 0.001, showing significant correlation with the reference. This proof-of-concept study successfully demonstrates that TFO can accurately differentiate maternal and fetal heart signals in human subjects. This achievement marks the initial step towards enabling fetal oxygen saturation measurement in humans using TFO., (© 2024. The Author(s), under exclusive licence to Society for Reproductive Investigation.)

Background: The utilization of non-invasive techniques for fetal cardiac health surveillance is pivotal in evaluating fetal well-being throughout the gestational period. This process requires clean and interpretable fetal Electrocardiogram (fECG) signals., Method: The proposed work is the novel framework for the elicitation of fECG signals from abdominal ECG (aECG) recordings of the pregnant mother. The comprehensive approach encompasses pre-processing of the raw ECG signal, Blind Source Separation techniques (BSS), Decomposition techniques like Empirical Mode Decomposition (EMD), and its variants like Ensemble Empirical Mode Decomposition (EEMD), and Complete Ensemble Empirical Mode Decomposition with Additive Noise (CEEMDAN). The Robust Set Membership Affine Projection (RSMAP) Algorithm is deployed for the enhancement of the obtained fECG signal., Result: The results show significant improvements in the elicited fECG signal with a maximum Signal Noise Ratio (SNR) of 31.72 dB and correlation coefficient = 0.899, Maximum Heart Rate(MHR) obtained in the range of 108-142 bpm for all the records of abdominal ECG signals. The statistical test gave a p-value of 0.21 accepting the null hypothesis. The Abdominal and Direct Fetal Electrocardiogram Database (ABDFECGDB) from PhysioNet has been used for this analysis., Conclusion: The proposed framework demonstrates a robust and effective method for the elicitation and enhancement of fECG signals from the abdominal recordings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: To identify new parameters predicting fetal acidemia., Methods: A retrospective case-control study in a cohort of deliveries from a tertiary referral hospital-based cohort deliveries in Zaragoza, Spain between 2018 and 2021 was performed. To predict fetal acidemia, the NICHD categorizations and non-NICHD parameters were analyzed in the electronic fetal monitoring (EFM). Those included total reperfusion time, total deceleration area and the slope of the descending limb of the fetal heart rate of the last deceleration curve. The accuracy of the parameters was evaluated using the specificity for (80%, 85%, 90%, 95%) sensitivity and the area under the receiver operating characteristic curve (AUC)., Results: A total of 10 362 deliveries were reviewed, with 224 cases and 278 controls included in the study. The NICHD categorizations showed reasonable discriminatory ability (AUC = 0.727). The non-NICHD parameters measured during the 30-min fetal monitoring, total deceleration area (AUC = 0.807, 95% CI: 0.770, 0.845) and total reperfusion time (AUC = 0.750, 95% CI: 0.707, 0.792), exhibited higher discriminatory ability. The slope of the descending limb of the fetal heart rate of the last deceleration curve had the best AUC value (0.853, 95% CI: 0.816, 0.889). The combination of total deceleration area or total reperfusion time with the slope demonstrated high discriminatory ability (AUC = 0.908, 95% CI: 0.882, 0.933; specificities of 71.6% and 72.7% for a sensitivity of 90%)., Conclusions: The slope of the descending limb of the fetal heart rate of the last deceleration curve is the strongest predictor of fetal acidosis, but its combination with the total reperfusion time shows better clinical utility., (© 2024 The Authors. International Journal of Gynecology & Obstetrics published by John Wiley & Sons Ltd on behalf of International Federation of Gynecology and Obstetrics.)

Objective: To construct algorithms with a sequential decision analysis pathway for monitoring of the fetal heart rate and managing fetal heart rate bradycardia, late decelerations and tachycardia during labour., Population: Low-risk pregnant women in labour with singleton cephalic term pregnancies., Setting: Institutional births in low- and middle-income countries., Search Strategy: We sought relevant published clinical algorithms, guidelines and randomised trials/reviews by searching the Cochrane Library, PubMed and Google on the terms: "fetal AND heart AND rate AND algorithm AND (labour OR intrapartum)", up to March 2020., Case Scenarios: The two scenarios included were fetal heart rate bradycardia or late decelerations (potentially related to uterine rupture, placental abruption, cord prolapse, maternal hypotension, uterine hyperstimulation or unexplained) and fetal heart rate tachycardia (potentially related to maternal hyperthermia, infection, dehydration or unexplained). The algorithms provide pathways for definition, assessment, diagnosis, interventions to correct the abnormalities and ongoing monitoring leading to mode of birth, and linking to other algorithms in the series., Conclusions: The algorithms provide a framework for monitoring and managing fetal heart rate bradycardia, late decelerations and tachycardia during labour. We emphasise the inherent diagnostic inaccuracy of fetal heart rate monitoring, the tendency to over-diagnose fetal compromise, the need to consider fetal heart rate information in the context of other clinical features and the need to engage in informed, shared, family-centred decision-making. We note the need for further research on methods of fetal assessment during labour including clinical fetal arousal testing and the rapid biophysical profile test., Tweetable Abstract: Decision analysis algorithms for fetal bradycardia, late decelerations and tachycardia highlight diagnostic limitations., (© 2022 John Wiley & Sons Ltd.)

Objective. Even though the electrocardiogram (ECG) has potential to be used as a monitoring or diagnostic tool for fetuses, the use of non-invasive fetal ECG is complicated by relatively high amounts of noise and fetal movement during the measurement. Moreover, machine learning-based solutions to this problem struggle with the lack of clean reference data, which is difficult to obtain. To solve these problems, this work aims to incorporate fetal rotation correction with ECG denoising into a single unsupervised end-to-end trainable method. Approach. This method uses the vectorcardiogram (VCG), a three-dimensional representation of the ECG, as an input and extends the previously introduced Kalman-LISTA method with a Kalman filter for the estimation of fetal rotation, applying denoising to the rotation-corrected VCG. Main results. The resulting method was shown to outperform denoising auto-encoders by more than 3 dB while achieving a rotation tracking error of less than 33 ∘ . Furthermore, the method was shown to be robust to a difference in signal to noise ratio between electrocardiographic leads and different rotational velocities. Significance. This work presents a novel method for the denoising of non-invasive abdominal fetal ECG, which may be trained unsupervised and simultaneously incorporates fetal rotation correction. This method might prove clinically valuable due the denoised fetal ECG, but also due to the method's objective measure for fetal rotation, which in turn might have potential for early detection of fetal complications., (Creative Commons Attribution license.)

Background: A variety of technologies are used to monitor fetal wellbeing in labour. Different types of fetal monitoring devices impact women's experiences of labour and birth., Aim: This review aims to understand how continuous electronic fetal monitoring (CEFM) influences women's experiences, with a focus on sense of control, active decision-making and mobility., Methods: A systematic search of the literature was conducted. Findings from qualitative, quantitative and mixed methods studies were analysed to provide a review of current evidence., Findings: Eighteen publications were included. The findings were synthesised into three themes: 'Feeling reassured versus anxious about the welfare of their baby', 'Feeling comfortable and free to be mobile versus feeling uncomfortable and restricted', and 'Feeling respected and empowered to make decisions versus feeling depersonalised with minimal control '. Women experienced discomfort and a lack of mobility as a result of some CEFM technologies. They often felt anxious and had mixed feelings about their baby's welfare whilst these were in use. Some women valued the data produced by CEFM technologies about the welfare of their baby. Many women experienced a sense of depersonalisation and lack of control whilst CEFM technologies were used., Discussion: Fetal monitoring technologies influence women's experiences of labour both positively and negatively. Wireless devices were associated with the most positive response as they enabled greater freedom of movement., Conclusion: The design of emerging fetal monitoring technologies should incorporate elements which foster freedom of movement, are comfortable and provide women with a sense of choice and control. The implementation of fetal monitoring that enables these elements should be prioritised by health professionals., Competing Interests: Conflict of interest There is no conflict of interest to declare., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objectives: The use of telemonitoring in healthcare is generally increasing. Women with complicated pregnancies are using telemonitoring as an alternative to conventional management, encompassing hospitalization or frequent outpatient clinic visits. However, there is sparse evidence on how pregnant women experience monitoring of their unborn babies at home. Women might feel uncomfortable with this responsibility, and moreover they might miss face-to-face contact with healthcare personnel., Study Design: The study setting was a Danish hospital with a tertiary obstetric unit attending approximately 3400 births annually. A qualitative study design with interview as method included 11 pregnant women with type 1 diabetes or Gestational Diabetes Mellitus. This design was used to investigate how pregnant women with complicated pregnancies experienced telemonitoring of the fetus. Reflexive thematic analysis was used to analyze the pregnant women's experiences of telemonitoring., Results: Women with type 1 diabetes or Gestational Diabetes Mellitus found the advantages of telemonitoring to outweigh the disadvantages. They experienced telemonitoring as time-saving and that telemonitoring decreased the level of stress. Moreover, telemonitoring supports positive collaboration with healthcare professionals. The women also experienced a lack of coordination of consultations between different departments at the hospital and challenges with timing, feedback, and technical issues. Moreover, the women requested an opportunity to discuss family formation and emotions., Conclusions: Pregnant women with type 1 diabetes or Gestational Diabetes Mellitus benefit from the use of telemonitoring. To further improve the implementation and use of telemonitoring clinical implications, consider how timing and coordination of care, technical equipment, and feedback mechanisms could be improved., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Objective: In 2019 the American College of Obstetricians and Gynecologists (ACOG) issued specific recommendations for performance of antepartum fetal surveillance (AFS) based on individual risk factors. As similar recommendations were already in place at our institution, we have evaluated the impact of AFS on stillbirth (SB) occurrence in a 5-year cohort., Methods: Retrospective cohort study of all deliveries between 7/1/2013 and 6/30/2018. Excluded were multiples, anomalous fetuses or newborns, and deliveries before 32 0/7 weeks' gestation. AFS was conducted from 32 weeks with a modified biophysical profile, with a complete biophysical profile as back-up for non-reactive non-stress tests. All cases of SB were prospectively identified and individually reviewed to verify the presence of risk factors, the results of fetal testing if done, and calculate the interval between last fetal test and delivery. The electronic medical records during the study period were queried to identify women who underwent AFS and those who did not. Chi-square was used to compare the rates of SB between the two groups., Results: 16,827 women fulfilled the study inclusion and exclusion criteria, 5711 (34%) had risk factors which prompted AFS; 37% had 2 or more risk factors. SB occurred in 1.8‰ of them (10/5711) (3 had 1 risk factor, 5 had 2, and 2 had 3 risk factors). Rates of SB at ≥32.0 weeks were similar between women who had AFS and those who did not (1.8 vs. 2.3‰, p  = 0.51, OR = 0.75, 95%CI 0.36-1.55). The false-negative rate at <7 days of a reassuring AFS among compliant women was 1.4‰ (8/5711). Rates of preterm delivery were similar in the tested vs untested population (6.5 vs. 6.0%, p  = 0.22)., Conclusion: Implementation of AFS in women with risk factors similar to those recommended by the ACOG may lower the risk of SB from 32 weeks to that of low-risk pregnancies.

In the extraction of fetal electrocardiogram (ECG) signal, due to the unicity of the scale of the U-Net same-level convolution encoder, the size and shape difference of the ECG characteristic wave between mother and fetus are ignored, and the time information of ECG signals is not used in the threshold learning process of the encoder's residual shrinkage module. In this paper, a method of extracting fetal ECG signal based on multi-scale residual shrinkage U-Net model is proposed. First, the Inception and time domain attention were introduced into the residual shrinkage module to enhance the multi-scale feature extraction ability of the same level convolution encoder and the utilization of the time domain information of fetal ECG signal. In order to maintain more local details of ECG waveform, the maximum pooling in U-Net was replaced by Softpool. Finally, the decoder composed of the residual module and up-sampling gradually generated fetal ECG signals. In this paper, clinical ECG signals were used for experiments. The final results showed that compared with other fetal ECG extraction algorithms, the method proposed in this paper could extract clearer fetal ECG signals. The sensitivity, positive predictive value, and F1 scores in the 2013 competition data set reached 93.33%, 99.36%, and 96.09%, respectively, indicating that this method can effectively extract fetal ECG signals and has certain application values for perinatal fetal health monitoring.

Fetal movement is a crucial indicator of fetal well-being. Characteristics of fetal movement vary across gestation, posing challenges for researchers to determine the most suitable assessment of fetal movement for their study. We summarize the current measurement strategies used to assess fetal movement and conduct a comprehensive review of studies utilizing these methods. We critically evaluate various measurement approaches including subjective maternal perception, ultrasound, Doppler ultrasound, wearable technology, magnetocardiograms, and magnetic resonance imaging, highlighting their strengths and weaknesses. We discuss the challenges of accurately capturing fetal movement, which is influenced by factors such as differences in recording times, gestational ages, sample sizes, environmental conditions, subjective perceptions, and characterization across studies. We also highlight the clinical implications of heterogeneity in fetal movement assessment for monitoring fetal behavior, predicting adverse outcomes, and improving maternal attachment to the fetus. Lastly, we propose potential areas of future research to overcome the current gaps and challenges in measuring and characterizing abnormal fetal movement. Our review contributes to the growing body of literature on fetal movement assessment and provides insights into the methodological considerations and potential applications for research., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective: The aim of this study was to explore the parents' experiences of home monitoring of the fetal heart rhythm. Women with anti-SSA/Ro52 autoantibodies carry a 2%-3% risk of giving birth to a child with congenital heart block (CHB), following transplacental transfer and antibody-mediated inflammation in the fetal conduction system during 18th to 24th gestational week. Early detection and subsequent treatment have been reported to decrease morbidity and mortality. Therefore, home monitoring of the fetal heart rhythm by Doppler has been offered at our fetal cardiology center. This study was undertaken to explore the lived experience of the routine., Methods: Participants were recruited from a single fetal cardiology center. Consecutive sampling was used. The inclusion criteria were women with SSA/Ro52 antibodies who had undergone Doppler examinations within the last two and a half years at the hospital and had monitored the fetal heartbeat at home. A semi-structured questionnaire was created, and the participants were interviewed individually. The interviews were transcribed verbatim and analyzed according to qualitative content analysis., Results: The overall theme was defined as "walking on thin ice," with six underlying categories: reality, different strategies, gain and loss, healthcare providers, underlying tension, and conducting the examinations again, all with a focus on how to handle the home monitoring during the risk period., Conclusion: Both the mother and the co-parent expressed confidence in their own abilities and that the monitoring provided them with the advantage of growing a bond with the expected child. However, all the participants described a feeling of underlying tension during the risk period. The results show that home monitoring is not experienced as complicated or a burden for the parents-to-be and should be considered a vital part of the chain of care for mothers at risk for giving birth to a child with CHB. However, explaining the teamwork between the different caregivers, for the patients involved, their areas of expertise, and how they collaborate with the patient continues to be a pedagogic challenge and should be developed further., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background and Objective: Obstetricians use Cardiotocography (CTG), which is the continuous recording of fetal heart rate and uterine contraction, to assess fetal health status. Deep learning models for intelligent fetal monitoring trained on extensively labeled and identically distributed CTG records have achieved excellent performance. However, creation of these training sets requires excessive time and specialist labor for the collection and annotation of CTG signals. Previous research has demonstrated that multicenter studies can improve model performance. However, models trained on cross-domain data may not generalize well to target domains due to variance in distribution among datasets. Hence, this paper conducted a multicenter study with Deep Semi-Supervised Domain Adaptation (DSSDA) for intelligent interpretation of antenatal CTG signals. This approach helps to align cross-domain distribution and transfer knowledge from a label-rich source domain to a label-scarce target domain., Methods: We proposed a DSSDA framework that integrated Minimax Entropy and Domain Invariance (DSSDA-MMEDI) to reduce inter-domain gaps and thus achieve domain invariance. The networks were developed using GoogLeNet to extract features from CTG signals, with fully connected, softmax layers for classification. We designed a Dynamic Gradient-driven strategy based on Mutual Information (DGMI) to unify the losses from Minimax Entropy (MME), Domain Invariance (DI), and supervised cross-entropy during iterative learning., Results: We validated our DSSDA model on two datasets collected from collaborating healthcare institutions and mobile terminals as the source and target domains, which contained 16,355 and 3,351 CTG signals, respectively. Compared to the results achieved with deep learning networks without DSSDA, DSSDA-MMEDI significantly improved sensitivity and F1-score by over 6%. DSSDA-MMEDI also outperformed other state-of-the-art DSSDA approaches for CTG signal interpretation. Ablation studies were performed to determine the unique contribution of each component in our DSSDA mechanism., Conclusions: The proposed DSSDA-MMEDI is feasible and effective for alignment of cross-domain data and automated interpretation of multicentric antenatal CTG signals with minimal annotation cost., Competing Interests: Declaration of Competing Interest The authors declare that they have no known financial and personal relationships which could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Standard clinical practice to assess fetal well-being during labour utilises monitoring of the fetal heart rate (FHR) using cardiotocography. However, visual evaluation of FHR signals can result in subjective interpretations leading to inter and intra-observer disagreement. Therefore, recent studies have proposed deep-learning-based methods to interpret FHR signals and detect fetal compromise. These methods have typically focused on evaluating fixed-length FHR segments at the conclusion of labour, leaving little time for clinicians to intervene. In this study, we propose a novel FHR evaluation method using an input length invariant deep learning model (FHR-LINet) to progressively evaluate FHR as labour progresses and achieve rapid detection of fetal compromise. Using our FHR-LINet model, we obtained approximately 25% reduction in the time taken to detect fetal compromise compared to the state-of-the-art multimodal convolutional neural network while achieving 27.5%, 45.0%, 56.5% and 65.0% mean true positive rate at 5%, 10%, 15% and 20% false positive rate respectively. A diagnostic system based on our approach could potentially enable earlier intervention for fetal compromise and improve clinical outcomes., (© 2024. The Author(s).)

Purpose of Review: Nonobstetric surgery during pregnancy is associated with maternal and fetal risks. Several physiologic changes create unique challenges for anesthesiologists. This review highlights physiologic changes of pregnancy and presents clinical recommendations based on recent literature to guide anesthetic management for the pregnant patient undergoing nonobstetric surgery., Recent Findings: Nearly every anesthetic technique has been safely used in pregnant patients. Although it is difficult to eliminate confounding factors, exposure to anesthetics could endanger fetal brain development. Perioperative fetal monitoring decisions require an obstetric consult based on anticipated maternal and fetal concerns. Given the limitations of fasting guidelines, bedside gastric ultrasound is useful in assessing aspiration risk in pregnant patients. Although there is concern about appropriateness of sugammadex for neuromuscular blockade reversal due its binding to progesterone, preliminary literature supports its safety., Summary: These recommendations will equip anesthesiologists to provide safe care for the pregnant patient and fetus undergoing nonobstetric surgery., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Objective. Perinatal asphyxia poses a significant risk to neonatal health, necessitating accurate fetal heart rate monitoring for effective detection and management. The current gold standard, cardiotocography, has inherent limitations, highlighting the need for alternative approaches. The emerging technology of non-invasive fetal electrocardiography shows promise as a new sensing technology for fetal cardiac activity, offering potential advancements in the detection and management of perinatal asphyxia. Although algorithms for fetal QRS detection have been developed in the past, only a few of them demonstrate accurate performance in the presence of noise and artifacts. Approach. In this work, we propose Power-MF , a new algorithm for fetal QRS detection combining power spectral density and matched filter techniques. We benchmark Power-MF against three open-source algorithms on two recently published datasets (Abdominal and Direct Fetal ECG Database: ADFECG, subsets B1 Pregnancy and B2 Labour; Non-invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research: NInFEA). Main results. Our results show that Power-MF outperforms state-of-the-art algorithms on ADFECG (B1 Pregnancy: 99.5% ± 0.5% F1-score, B2 Labour: 98.0% ± 3.0% F1-score) and on NInFEA in three of six electrode configurations by being more robust against noise. Significance. Through this work, we contribute to improving the accuracy and reliability of fetal cardiac monitoring, an essential step toward early detection of perinatal asphyxia with the long-term goal of reducing costs and making prenatal care more accessible., (Creative Commons Attribution license.)

Qualitative research about women and birthing people's experiences of fetal monitoring during labour and birth is scant. Labour and birth is often impacted by wearable or invasive monitoring devices, however, most published research about fetal monitoring is focused on the wellbeing of the fetus. This manuscript is derived from a larger mixed methods study, 'WOmen's Experiences of Monitoring Baby (The WOMB Study)', aiming to increase understanding of the experiences of women and birthing people in Australia, of being monitored; and about the information they received about fetal monitoring devices during pregnancy. We constructed a national cross-sectional survey that was distributed via social media in May and June, 2022. Responses were received from 861 participants. As far as we are aware, this is the first survey of the experiences of women and birthing people of intrapartum fetal monitoring conducted in Australia. This paper comprises the analysis of the free text survey responses, using qualitative and inductive content analysis. Two categories were constructed, Tending to the machine, which explores participants' perceptions of the way in which clinicians interacted with fetal monitoring technologies; and Impressions of the machine, which explores the direct impact of fetal monitoring devices upon the labour and birth experience of women and birthing people. The findings suggest that some clinicians need to reflect upon the information they provide to women and birthing people about monitoring. For example, freedom of movement is an important aspect of supporting the physiology of labour and managing pain. If freedom of movement is important, the physical restriction created by a wired cardiotocograph is inappropriate. Many participants noticed that clinicians focused their attention primarily on the technology. Prioritising the individual needs of the woman or birthing person is key to providing high quality woman-centred intrapartum care. Women should be provided with adequate information regarding the risks and benefits of different forms of fetal monitoring including how the form of monitoring might impact her labour experience., Competing Interests: I have read the journal’s policy and the first author of this manuscript (DF) has the following competing interests: Deborah Fox has received consultancy fees and research funding for other research projects from Philips Healthcare. Philips Healthcare did not fund this study and had no role in this study., (Copyright: © 2024 Fox et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The fetal electrocardiogram (FECG) records changes in the graph of fetal cardiac action potential during conduction, reflecting the developmental status of the fetus in utero and its physiological cardiac activity. Morphological alterations in the FECG can indicate intrauterine hypoxia, fetal distress, and neonatal asphyxia early on, enhancing maternal and fetal safety through prompt clinical intervention, thereby reducing neonatal morbidity and mortality. To reconstruct FECG signals with clear morphological information, this paper proposes a novel deep learning model, CBLS-CycleGAN. The model's generator combines spatial features extracted by the CNN with temporal features extracted by the BiLSTM network, thus ensuring that the reconstructed signals possess combined features with spatial and temporal dependencies. The model's discriminator utilizes PatchGAN, employing small segments of the signal as discriminative inputs to concentrate the training process on capturing signal details. Evaluating the model using two real FECG signal databases, namely "Abdominal and Direct Fetal ECG Database" and "Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeat Annotations", resulted in a mean MSE and MAE of 0.019 and 0.006, respectively. It detects the FQRS compound wave with a sensitivity, positive predictive value, and F 1 of 99.51%, 99.57%, and 99.54%, respectively. This paper's model effectively preserves the morphological information of FECG signals, capturing not only the FQRS compound wave but also the fetal P-wave, T-wave, P-R interval, and ST segment information, providing clinicians with crucial diagnostic insights and a scientific foundation for developing rational treatment protocols.

Fetal acidosis among low-risk pregnancies is not common; however, identifying those at risk for this complication antenatally is of great interest. We aimed to assess the correlation between the total decelerations area during the last 120 min of fetal monitoring prior to delivery and neonatal acidemia in low-risk pregnancies and whether the total acceleration area has a protective effect in the presence of decelerations. A retrospective cohort study was conducted among women with term low-risk pregnancies. A researcher blinded to fetal outcomes interpreted electronic fetal monitor patterns during the 120 min prior to delivery. The primary outcome was fetal acidemia, defined as umbilical artery pH below 7.10. The correlation between the total decelerations and accelerations areas and cord blood pH was tested using the Spearman correlation coefficient. A total of 109 women were included and of these, six (5.5%) delivered infants with cord blood pH < 7.10. A significant correlation was demonstrated between the total decelerations area and cord blood pH (p = 0.01). No correlation was found between the total accelerations area and cord blood pH. Among low-risk pregnancies, a correlation was found between the total decelerations area but not the total accelerations area during the final 120 min of labor and cord blood pH., (© 2024. The Author(s), under exclusive licence to Society for Reproductive Investigation.)

Objective: To examine whether a correlation exists between electronic fetal monitoring (EFM) in the final 120 minute prior to delivery and neonatal cord blood pH among parturients with preeclampsia., Study Design: A retrospective cohort study of parturients with term and near-term preeclampsia who delivered at Soroka University Medical Center between 2013 and 2020 was conducted. EFM tracings, demographical data, and obstetrical outcomes were retrieved from the patients' electronic medical records. Using MATLAB program, area under the curve (AUC) measurements were applied. Correlation was calculated using the Spearman's correlation coefficient., Results: EFM of 88 parturients with preeclampsia were assessed. A significant negative correlation was demonstrated between cord blood pH and the decelerations AUC, total decelerations duration, and deceleration depth. No correlation was demonstrated between area over the curve (acceleration) and cord blood pH. In a multivariate linear regression, total deceleration AUC was found independently negatively associated with cord blood pH (beta = -0.264, p  = 0.011) controlling for second stage of labor duration and induction of labor., Conclusion: Among parturients with preeclampsia, EFM indices may assist in the diagnosis of fetal acidemia. Further studies are needed to strengthen and establish the use of electronic EFM in the management of labor and delivery., Key Points: · A negative correlation was demonstrated between cord blood pH and the decelerations AUC.. · Total deceleration AUC was found independently negatively associated.. · Among parturients with preeclampsia, EFM indices may assist in the diagnosis of fetal acidemia.., Competing Interests: None declared., (Thieme. All rights reserved.)

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., (© 2024 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).)

Intermittent auscultation (IA) is an evidence-based method of fetal surveillance during labor for birthing people with low-risk pregnancies. It is a central component of efforts to reduce the primary cesarean rate and promote vaginal birth (American College of Obstetricians and Gynecologists, 2019; Association of Women's Health, Obstetric and Neonatal Nurses, 2022a). The use of intermittent IA decreased with the introduction of electronic fetal monitoring, while the increased use of electronic fetal monitoring has been associated with an increase of cesarean births. This practice monograph includes information on IA techniques; interpretation and documentation; clinical decision-making and interventions; communication; education, staffing, legal issues; and strategies to implement IA., (Copyright © 2023. Published by Elsevier Inc.)

Objective: This study aimed to measure the proportion of patients needing urgent clinical follow-up after an abnormal outpatient nonstress test (NST). We further sought to capture the patient perspective on the acceptability of performing NSTs at home., Study Design: A retrospective cohort study was performed over a 2-year period to determine the frequency of abnormal NSTs in a hospital-based, antepartum testing unit in patients greater than or equal to 32 weeks' gestation. The proportion of patients who delivered within 24 hours of an abnormal NST was also determined. A cross-sectional, web-based patient survey was conducted to obtain insight into the patient's comfort level with potentially performing NSTs at home., Results: The chart review yielded 665 patients who underwent 2,122 NSTs at greater than or equal to 32 weeks. Of the 2,122 NSTs, 111 were categorized as abnormal and required urgent clinical follow-up, or 5.2% (95% confidence interval [CI] 4.3, 6.3%). Of the 665 patients, 13 delivered within 24 hours of an abnormal NST, or 2.0% (95% CI 1.0, 3.3%). In the web-based survey, the proportion of respondents who would feel comfortable or very comfortable conducting NSTs at home was 87/125, or 69.6% (95% CI 60.9, 77.1%)., Conclusion: This study revealed that 5.2% of NSTs performed in a hospital-based antepartum testing unit were abnormal and required urgent clinical follow-up. Of the patients being followed in the antepartum testing unit, 2.0% delivered within 24 hours of an abnormal NST. The majority of the survey respondents indicated they would feel comfortable performing NSTs at home. The present study adds important information regarding the risks and benefits of NSTs at home., Key Points: · Telehealth for NSTs offers advantages over in-person NSTs.. · The proportion of NSTs that need urgent follow-up was 5.2%.. · A majority of patients are interested in telehealth for NSTs.. · Guidelines are needed before adoption of telehealth for NSTs.., Competing Interests: None declared., (Thieme. All rights reserved.)

Purpose:  The aim of this guideline was to find evidence on whether carrying out Doppler examinations and CTGs in low-risk cohorts of pregnant women improves outcomes., Methods:  First, a systematic search for guidelines was carried out. Identified guidelines were evaluated using the DELPHI instrument of the AWMF. Three guidelines were found to be suitable to evaluate CTG. Two DEGUM best practice guidelines were judged suitable to describe the methods. All studies on this issue were additionally analyzed using 8 PICO questions. A structured consensus of the participating professional societies was achieved using a nominal group process and a structured consensus conference moderated by an independent moderator., Recommendations:  No antepartum Doppler sonography examinations should be carried out in low-risk cohorts in the context of antenatal care. No antepartum CTG should be carried out in low-risk cohorts. NOTE:  The guideline will be published simultaneously in the official journals of both professional societies (i. e., Geburtshilfe und Frauenheilkunde for the DGGG and Ultraschall in der Medizin/European Journal of Ultrasound for the DEGUM)., Competing Interests: The conflicts of interest of all the authors are listed in the German-language long version of the guideline., (Thieme. All rights reserved.)

Introduction: ST waveform analysis (STAN) was introduced as an adjunct to cardiotocography (CTG) to improve neonatal and maternal outcomes. The aim of the present study was to quantify the efficacy of STAN vs CTG and assess the quality of the evidence using GRADE., Material and Methods: We performed systematic literature searches to identify randomized controlled trials and assessed included studies for risk of bias. We performed meta-analyses, calculating pooled risk ratio (RR) or Peto odds ratio (OR). We also performed post hoc trial sequential analyses for selected outcomes to assess the risk of false-positive results and the need for additional studies., Results: Nine randomized controlled trials including 28 729 women were included in the meta-analysis. There were no differences between the groups in operative deliveries for fetal distress (10.9 vs 11.1%; RR 0.96; 95% confidence interval [CI] 0.82-1.11). STAN was associated with a significantly lower rate of metabolic acidosis (0.45% vs 0.68%; Peto OR 0.66; 95% CI 0.48-0.90). Accordingly, 441 women need to be monitored with STAN instead of CTG alone to prevent one case of metabolic acidosis. Women allocated to STAN had a reduced risk of fetal blood sampling compared with women allocated to conventional CTG monitoring (12.5% vs 19.6%; RR 0.62; 95% CI 0.49-0.80). The quality of the evidence was high to moderate., Conclusions: Absolute effects of STAN were minor and the clinical significance of the observed reduction in metabolic acidosis is questioned. There is insufficient evidence to state that STAN as an adjunct to CTG leads to important clinical benefits compared with CTG alone., (© 2023 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).)

Monitoring the fetal heartbeat underpins assessment of fetal wellbeing in labour. Although commonly employed in clinical practice, shortcomings remain. A recent review of clinical practice guidelines highlights the variation in definitions of the fetal heart rate that will lead to differences in interpretation. Will intrapartum care be improved by greater consensus around clinical practice guidelines through rationalisation or refinement of guidelines, or will the future see this technique replaced by more accurate forms of fetal monitoring?, (© 2023 Royal Australian and New Zealand College of Obstetricians and Gynaecologists.)

Objective: The objective of this study was to compare performance of a maternal surface electrode patch with ultrasound- and tocodynamometer-based monitoring to detect fetal heart rate and uterine contractility in late preterm labors., Study Design: Thirty women between 34 0/7 and 36 6/7 weeks' gestation were monitored simultaneously with a Doppler/tocodynamometer system and a wireless fetal-maternal abdominal surface electrode system. Fetal and maternal heart rate and uterine contraction data from both systems were compared. Reliability was measured by the success rate and percent agreement. Deming regression and Bland-Altman analysis estimated the concordance between the systems. Uterine contractions were assessed by visual interpretation of monitor tracings., Results: The success rate for the surface electrode system was 89.5% (95% confidence interval [CI], 85.7-93.3), and for ultrasound it was 88.4% (95% CI, 84.9-91.9; p  = 0.73), with a percent agreement of 88.1% (95% CI, 84.2-92.8). Results were uninfluenced by the patients' body mass. The mean Deming slope was 1 and the y-intercept was -3.0 beats per minute (bpm). Bland-Altman plots also showed a close relationship between the methods, with limits of agreement less than 10 bpm. The percent agreement for maternal heart rate was 98.2% (95% CI, 97.4-98.8), and for uterine contraction detection it was 89.5% (95% CI, 85.5-93.4)., Conclusion: Fetal heart rate and uterine contraction monitoring at 34 0/7 to 36 6/7 weeks using abdominal surface electrodes was not inferior to Doppler ultrasound/tocodynamometry for fetal-maternal assessment., Registration: clinicaltrials.gov/February 20, 2017/identifier NCT03057275., Key Points: · Monitoring the preterm fetal heart rate with surface electrodes is feasible.. · Preterm contractions can be monitored with surface electrodes.. · The technique was noninferior to standard external monitors.., Competing Interests: M. G. and M. H. report no relevant conflict of interest. W. R. C. was previously a paid consultant to Monica Healthcare, Ltd., and to General Electric Healthcare. He is no longer affiliated with either., (Thieme. All rights reserved.)

Intrapartum fetal hypoxia is related to long-term morbidity and mortality of the fetus and the mother. Fetal surveillance is extremely important to minimize the adverse outcomes arising from fetal hypoxia during labour. Several methods have been used in current clinical practice to monitor fetal well-being. For instance, biophysical technologies including cardiotocography, ST-analysis adjunct to cardiotocography, and Doppler ultrasound are used for intrapartum fetal monitoring. However, these technologies result in a high false-positive rate and increased obstetric interventions during labour. Alternatively, biochemical-based technologies including fetal scalp blood sampling and fetal pulse oximetry are used to identify metabolic acidosis and oxygen deprivation resulting from fetal hypoxia. These technologies neither improve clinical outcomes nor reduce unnecessary interventions during labour. Also, there is a need to link the physiological changes during fetal hypoxia to fetal monitoring technologies. The objective of this article is to assess the clinical background of fetal hypoxia and to review existing monitoring technologies for the detection and monitoring of fetal hypoxia. A comprehensive review has been made to predict fetal hypoxia using computational and machine-learning algorithms. The detection of more specific biomarkers or new sensing technologies is also reviewed which may help in the enhancement of the reliability of continuous fetal monitoring and may result in the accurate detection of intrapartum fetal hypoxia., (Creative Commons Attribution license.)

Introduction: No evidence-based protocols exist for fetal cardiac monitoring during fetoscopic myelomeningocele (fMMC) repair and intraprocedural spectral Doppler data are limited. We determined the feasibility of continuous fetal echocardiography during fMMC repair and correlated Doppler changes with qualitative fetal cardiac function during each phase of fMMC repair., Methods: Patients undergoing fMMC repair had continuous fetal echocardiography interpreted in real-time by pediatric cardiology. Fetal data included fetal heart rate (FHR), qualitative cardiac function, mitral and tricuspid valve inflow waveforms, and umbilical artery (UA), umbilical vein (UV), ductus arteriosus (DA), and ductus venosus (DV) Dopplers., Results: UA abnormalities were noted in 14/25 patients, UV abnormalities were observed in 2 patients, and DV and DA abnormalities were each noted in 4 patients. Qualitative cardiac function was normal for all patients with the exception of one with isolated left ventricular dysfunction during myofascial flap creation, concurrent with an abnormal UA flow pattern. All abnormalities resolved by the first postoperative day., Conclusions: Continuous fetal echocardiography was feasible during all fMMC repairs. Spectral Doppler changes in the UA were common during fMMC procedures but qualitative cardiac dysfunction was rare. Abnormalities in the UV, DV, and DA Dopplers, FHR, and cardiac function were less common findings., (© 2024 S. Karger AG, Basel.)

Introduction: It is a shortcoming of traditional cardiotocography (CTG) classification table formats that CTG traces are frequently classified differently by different users, resulting in poor interobserver agreements. A fast-and-frugal tree (FFTree) flow chart may help provide better concordance because it is straightforward and has clearly structured binary questions with understandable "yes" or "no" responses. The initial triage to determine whether a fetus is suitable for labor when utilizing fetal ECG ST analysis (STAN) is very important, since a fetus with restricted capacity to respond to hypoxic stress may not generate STAN events and therefore may become falsely negative. This study aimed to compare physiology-focused FFTree CTG interpretation with FIGO classification for assessing the suitability for STAN monitoring., Material and Methods: A retrospective study of 36 CTG traces with a high proportion of adverse outcomes (17/36) selected from a European multicenter study database. Eight experienced European obstetricians evaluated the initial 40 minutes of the CTG recordings and judged whether STAN was a suitable fetal surveillance method and whether intervention was indicated. The experts rated the CTGs using the FFTree and FIGO classifications at least 6 weeks apart. Interobserver agreements were calculated using proportions of agreement and Fleiss' kappa (κ)., Results: The proportions of agreement for "not suitable for STAN" were for FIGO 47% (95% confidence interval [CI] 42%-52%) and for FFTree 60% (95% CI 56-64), ie a significant difference; the corresponding figures for "yes, suitable" were 74% (95% CI 71-77) and 70% (95% CI 67-74). For "intervention needed" the figures were 52% (95% CI 47-56) vs 58% (95% CI 54-62) and for "expectant management" 74% (95% CI 71-77) vs 72% (95% CI 69-75). Fleiss' κ agreement on "suitability for STAN" was 0.50 (95% CI 0.44-0.56) for the FIGO classification and 0.57 (95% CI 0.51-0.63) for the FFTree classification; the corresponding figures for "intervention or expectancy" were 0.53 (95% CI 0.47-0.59) and 0.57 (95% CI 0.51-0.63)., Conclusions: The proportion of agreement among expert obstetricians using the FFTree physiological approach was significantly higher compared with the traditional FIGO classification system in rejecting cases not suitable for STAN monitoring. That might be of importance to avoid false negative STAN recordings. Other agreement figures were similar. It remains to be shown whether the FFTree simplicity will benefit less experienced users and how it will work in real-world clinical scenarios., (© 2023 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).)

Combined the improved fast independent component analysis (FastICA) algorithm with the singular value decomposition algorithm, a single-channel fetal electrocardiogram (fECG) extraction method is proposed. First, the improved FastICA algorithm is used to estimate the maternal ECG component from a single-channel abdominal signal of pregnant women using an overrelaxation factor. Then, a preliminary estimate of the fECG signal is obtained by subtracting from the single-channel abdominal signal. Subsequently, the singular value decomposition algorithm is used to denoise the preliminarily estimated fECG signal to obtain a high signal-to-noise ratio. In addition, in the singular value decomposition algorithm for fetal arrhythmia, an improved method for constructing the ECG signal reconstruction matrix is proposed. Finally, the fECG extraction experiments on synthetic abdominal signals and actual abdominal signals (data from 49 abdominal channels sourced from DAISY database and the non-invasive fECG database in PhysioNet) are carried out. The experimental results show that the method in this paper can effectively improve the signal-to-noise ratio and the accuracy of fECG signal extraction, and is suitable for maternal or fetal arrhythmias. Compared with the FastICA algorithm, the signal-to-noise ratio of the fECG signal extracted by the method in this paper is improved by about 5 dB, and the accuracy of fECG extraction in the PhysioNet database can reach 96.54%.

To extract weak fetal ECG signals from the mixed ECG signal on the mother's abdominal wall, providing a basis for accurately estimating fetal heart rate and analyzing fetal ECG morphology. First, based on the relationship between the maternal chest ECG signal and the maternal ECG component in the abdominal signal, the temporal convolutional encoder-decoder network (TCED-Net) model is trained to fit the nonlinear transmission of the maternal ECG signal from the chest to the abdominal wall. Then, the maternal chest ECG signal is nonlinearly transformed to estimate the maternal ECG component in the abdominal mixed signal. Finally, the estimated maternal ECG component is subtracted from the abdominal mixed signal to obtain the fetal ECG component. The simulation results on the FECGSYN dataset show that the proposed approach achieves the best performance in F 1 score, mean square error (MSE), and quality signal-to-noise ratio (qSNR) (98.94%, 0.18, and 8.30, respectively). On the NI-FECG dataset, although the fetal ECG component is small in energy in the mixed signal, this method can effectively suppress the maternal ECG component and thus extract a clearer and more accurate fetal ECG signal. Compared with existing algorithms, the proposed method can extract clearer fetal ECG signals, which has significant application value for effective fetal health monitoring during pregnancy., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objective. Independent component analysis (ICA) is widely used in the extraction of fetal ECG (FECG). However, the amplitude, order, and positive or negative values of the ICA results are uncertain. The main objective is to present a novel approach to FECG recognition by using a deep learning strategy. Approach. A cross-domain consistent convolutional neural network (CDC-Net) is developed for the task of FECG recognition. The output of the ICA algorithm is used as input to the CDC-Net and the CDC-Net identifies which channel's signal is the target FECG. Main results. Signals from two databases are used to test the efficiency of the proposed method. The proposed deep learning method exhibits good performance on FECG recognition. Specifically, the Precision, Recall and F1-score of the proposed method on the ADFECGDB database are 91.69%, 91.37% and 91.52%, respectively. The Precision, Recall and F1-score of the proposed method on the Daisy database are 97.85%, 97.42% and 97.63%, respectively. Significance . This study is a proof of concept that the proposed method can automatically recognize the FECG signals in multi-channel ECG data. The development of FECG recognition technology contributes to automated FECG monitoring., (© 2023 Institute of Physics and Engineering in Medicine.)

Previous literature has highlighted the importance of maternal behavior during the prenatal period for the upbringing of healthy adults. During pregnancy, fetal health assessments are mainly carried out non-invasively by monitoring fetal growth and heart rate (HR) or RR interval (RRI). Despite this, research entailing prediction of fHRs from mHRs is scarce mainly due to the difficulty in non-invasive measurements of fetal electrocardiogram (fECG). Also, so far, it is unknown how mHRs are associated with fHR over the short term. In this study, we used two machine learning models, support vector regression (SVR) and random forest (RF), for predicting average fetal RRI (fRRI). The predicted fRRI values were compared with actual fRRI values calculated from non-invasive fECG. fRRI was predicted from 13 maternal features that consisted of age, weight, and non-invasive ECG-derived parameters that included HR variability (HRV) and R wave amplitude variability. 156 records were used for training the models and the results showed that the SVR model outperformed the RF model with a root mean square error (RMSE) of 29 ms and an average error percentage (< 5%). Correlation analysis between predicted and actual fRRI values showed that the Spearman coefficient for the SVR and RF models were 0.31 (P < 0.001) and 0.19 (P < 0.05), respectively. The SVR model was further used to predict fRRI of 14 subjects who were not included in the training. The latter prediction results showed that individual error percentages were (≤ 5%) except in 3 subjects. The results of this study show that maternal factors can be potentially used for the assessment of fetal well-being based on fetal HR or RRI., (© 2023. The Author(s).)

Background: Nonreassuring fetal status detected by continuous electronic fetal monitoring accounts for almost 1 in 4 primary cesarean deliveries. However, given the subjective nature of the diagnosis, there is a need to identify the electronic fetal monitoring patterns that are clinically considered nonreassuring., Objective: This study aimed to describe which electronic fetal monitoring features are most commonly associated with first-stage cesarean delivery for nonreassuring fetal status, and to evaluate the risk of neonatal acidemia following cesarean delivery for nonreassuring fetal status., Study Design: This was a nested case-control study in a prospectively collected cohort of patients with singleton pregnancies at ≥37 weeks' gestation, admitted in spontaneous labor or for induction of labor from 2010 to 2014 at a single tertiary care center. Patients with preterm pregnancies, multiple gestations, planned cesarean delivery, or nonreassuring fetal status in the second stage of labor were excluded. Cases were identified as having nonreassuring fetal status on the basis of what was documented in the operative note by the delivering physician. Controls were patients without nonreassuring fetal status within 1 hour of delivery. Cases were matched to controls in a 1:2 ratio by parity, obesity, and history of cesarean delivery. Electronic fetal monitoring data were abstracted by credentialed obstetrical research nurses for the 60 minutes before delivery. The primary exposure of interest was the incidence of high-risk category II electronic fetal monitoring features in the 60 minutes before delivery; in particular, the incidence of minimal variability, recurrent late decelerations, recurrent variable decelerations, tachycardia, and >1 prolonged deceleration were compared between groups. We also compared neonatal outcomes between cases and controls, including fetal acidemia (umbilical artery pH <7.1), other umbilical artery gas analytes, and neonatal and maternal outcomes., Results: Of the 8580 patients in the parent study, 714 (8.3%) underwent cesarean delivery for nonreassuring fetal status in the first stage of labor. Patients diagnosed with nonreassuring fetal status requiring cesarean delivery were more likely to have recurrent late decelerations, >1 prolonged deceleration, and recurrent variable decelerations compared with controls. More than 1 prolonged deceleration was associated with 6 times increased rate of nonreassuring fetal status diagnosis resulting in cesarean delivery (adjusted odds ratio, 6.73 [95% confidence interval, 2.47-8.33]). Rates of fetal tachycardia were similar between groups. Minimal variability was less common in the nonreassuring fetal status group compared with controls (adjusted odds ratio, 0.36 [95% confidence interval, 0.25-0.54]). Compared with control deliveries, cesarean delivery for nonreassuring fetal status was associated with nearly 7 times higher risk of neonatal acidemia (7.2% vs 1.1%; adjusted odds ratio, 6.93 [95% confidence interval, 3.83-12.54]). Composite neonatal morbidity and composite maternal morbidity were more likely among patients delivered for nonreassuring fetal status in the first stage (3.9% vs 1.1%; adjusted odds ratio, 5.70 [2.60-12.49]; and 13.3% vs 8.0%; adjusted odds ratio, 1.99 [1.41-2.80])., Conclusion: Although multiple category II electronic fetal monitoring features have been traditionally linked to acidemia, the presence of recurrent late decelerations, recurrent variable decelerations, and prolonged decelerations seemed to concern obstetricians enough to surgically intervene for nonreassuring fetal status. A clinical intrapartum diagnosis of nonreassuring fetal status in the setting of these electronic fetal monitoring features is also associated with increased risk of acidemia, suggesting clinical validity to the diagnosis of nonreassuring fetal status., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Previous studies have suggested that acute mood states may influence levels of fetal activity. Because the fetal nonstress test relies on markers of fetal activity to suggest fetal wellbeing, its interpretation may be affected by maternal mood., Objective: This study sought to determine if there are differences in nonstress test characteristics between pregnant individuals with and without symptoms of mood disorder., Study Design: In this prospective cohort study, we recruited pregnant individuals undergoing nonstress test in the third trimester and compared the results of the nonstress test between pregnant individuals with scores above and below the cutoff values on validated screening questionnaires for depression and anxiety symptoms, the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder 7-item scale (GAD-7). Demographic information was collected from each participant at the time of recruitment, and medical information was extracted from the electronic medical record., Results: A total of 68 pregnant individuals were enrolled, 10 (15%) of which screened positive for perinatal mood disorders. There was no significant difference in means of time to reactivity (15.6 [4.8] minutes vs 15.0 [8.0] minutes, P=.77), number of accelerations (0.16/min [0.08] vs 0.16/min [0.10], P>.95), number of fetal movements (17.0 [14.7] vs 19.7 [20.4], P=.62), heart rate baseline (138.0 [7.5] bpm vs 139.2 [9.0] bpm, P=.67) or variability (8.5 [2.5] bpm vs 9.1 (4.3) bpm, P=.51) between pregnant individuals who screen positive for mood disorders and those who did not., Conclusion: Fetal heart rate patterns are similar in pregnant individuals with and without symptoms of mood disorder. The results provide reassurance that acute symptoms of anxiety and depression do not have significant effects on the fetal nonstress test., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Electronic fetal monitoring is widely used to identify and intervene in suspected fetal hypoxia and/or acidemia. Category II fetal heart rate tracings are the most common class of fetal monitoring in labor, and intrauterine resuscitation is recommended given the association of category II fetal heart rate tracings with fetal acidemia. However, limited published data are available to guide intrauterine resuscitation technique selection, leading to heterogeneity in the response to category II fetal heart rate tracings., Objective: This study aimed to characterize approaches to intrauterine resuscitation in response to category II fetal heart rate tracings., Study Design: This was a survey study administered to labor unit nurses and delivering clinicians (physicians and midwives) across 7 hospitals in a Midwestern healthcare system spanning 2 states. The survey posed 3 category II fetal heart rate tracing scenarios (recurrent late decelerations, minimal variability, and recurrent variable decelerations) and asked participants to select first- and second-line intrauterine resuscitation management strategies. The participants were asked to quantify the level of influence certain factors have on their choice using a scale from 1 to 5. Intrauterine resuscitation strategy selection was compared by clinical role and hospital type (nurses vs delivering clinicians and university-affiliated hospital vs non-university-affiliated hospital)., Results: Of 610 providers invited to take the survey, 163 participated (response rate of 27%): 37% of participants from university-affiliated hospitals, 62% of nurses, and 37% of physicians. Maternal repositioning was the most selected first-line strategy, regardless of the type of category II fetal heart rate tracing. First-line management varied by clinical role and hospital affiliation for each fetal heart rate tracing scenario, particularly for minimal variability, which was associated with the most heterogeneity in the first-line approach. Previous experience and recommendations from professional societies were the most influential factors in intrauterine resuscitation selection overall. Of note, 16.5% of participants reported that published evidence did not influence their choice at all. Participants from a university-affiliated hospital were more likely than participants from a non-university-affiliated hospital to consider patient preference when selecting an intrauterine resuscitation technique. Nurses and delivering clinicians differed significantly in the rationale for management choices: nurses were more often influenced by advice from other healthcare providers on the team (P<.001), whereas delivering clinicians were more influenced by literature (P=.02) and ease of technique (P=.02)., Conclusion: There was significant heterogeneity in the management of category II fetal heart rate tracing. In addition, motivations for choice in intrauterine resuscitation technique varied by hospital type and clinical role. These factors should be considered when creating fetal monitoring and intrauterine resuscitation protocols., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Fetal cardiac monitoring is very helpful in the early detection of the potential risk of fetal cardiac abnormalities, which enables prompt preventative care and ensures safe births. As a result, it is crucial to regularly check on the embryonic heart. Methods of non-invasively fetal ECG extraction from maternal abdominal ECG signal are thoroughly discussed. Although fetal signals are generally obscured by maternal ECG signals and noise, extracting a clean fetal ECG is a significant difficulty. The majority of techniques for fetal ECG extraction include many extraction steps. We describe a unique method for splitting a single-channel maternal abdominal ECG into maternal and fetus ECG employing two parallel U-nets with transformer encoding, which we refer to as W-NEt TRansformers (W-NETR). Due to its enhanced capacity to simulate remote interactions and capture global context, the suggested pipeline utilizes the self-attention mechanism of the transformer. We tested the proposed pipeline on synthetic and real datasets and outperformed the current state-of-the-art deep learning models. The proposed model achieved the best results on both datasets for QRS detection precision, recall, and F1 scores. More specifically, it achieved F1 score of 99.88% and 98.9% on the real ADFECGDB and PCDB datasets, respectively. These encouraging results highlight the suggested W-NETR's effectiveness in precisely extracting the fetal ECG, which was achieved with high SSIM and PSNR values in the results. This provides the bed set for long-term maternal and fetal monitoring via portable devices as the proposed system performs real-time execution.

Objective: Fetal heart rate (FHR) is critical for perinatal fetal monitoring. However, motions, contractions and other dynamics may substantially degrade the quality of acquired signals, hindering robust tracking of FHR. We aim to demonstrate how use of multiple sensors can help overcome these challenges., Methods: We develop KUBAI 1 , a novel stochastic sensor fusion algorithm, to improve FHR monitoring accuracy. To demonstrate the efficacy of our approach, we evaluate it on data collected from gold standard large pregnant animal models, using a novel non-invasive fetal pulse oximeter., Results: The accuracy of the proposed method is evaluated against invasive ground-truth measurements. We obtained below 6 beats-per-minute (BPM) root-mean-square error (RMSE) with KUBAI, on five different datasets. KUBAI's performance is also compared against a single-sensor version of the algorithm to demonstrate the robustness due to sensor fusion. KUBAI's multi-sensor estimates are found to give overall 23.5% to 84% lower RMSE than single-sensor FHR estimates. The mean ± SD of improvement in RMSE is 11.95 ±9.62 BPM across five experiments. Furthermore, KUBAI is shown to have 84% lower RMSE and  ∼ 3 times higher R 2 correlation with reference compared to another multi-sensor FHR tracking method found in literature., Conclusion: The results support the effectiveness of KUBAI, the proposed sensor fusion algorithm, to non-invasively and accurately estimate fetal heart rate with varying levels of noise in the measurements., Significance: The presented method can benefit other multi-sensor measurement setups, which may be challenged by low measurement frequency, low signal-to-noise ratio, or intermittent loss of measured signal.

Fetal electrocardiogram (fECG) or photoplethysmogram (fPPG) devices are being developed for fetal heart rate (FHR) monitoring. However, deep tissue sensing is challenged by low fetal signal-to-noise ratio (SNR). Data quality is easily degraded by motion, or interference from maternal tissues and data losses can happen due to communication faults. In this paper, we propose to combine fECG and fPPG measurements in order to increase robustness against such dynamic challenges and increase FHR estimation accuracy. To the author's knowledge the fusion of two sensory data types (fECG, fPPG) has not been investigated for FHR tracking purposes in the literature. The proposed methods are evaluated on real-world data captured from gold-standard large pregnant animal experiments. A particle filtering algorithm with sensor fusion in the measurement likelihood, called KUBAI, is used to estimate FHR. Fusion of PPG&ECG data resulted in 36.6% improvement in root-mean-square-error (RMSE) and 20.3% improvement in R 2 correlation between estimated and reference FHR values compared to single sensor-type (PPG-only or ECG-only) data. We demonstrate that using different types of sensory data improves the robustness and accuracy of FHR tracking.

Non-invasive fetal electrocardiography (NI-fECG) is a promising technique for continuous fetal heart rate (fHR) monitoring. However, the weak amplitude of the fetal electrocardiogram (fECG), and the presence of the dominant maternal ECG (mECG), makes it highly challenging to detect the fetal QRS (fQRS) complex, which is needed to obtain the fHR. This paper proposes a new method for automated fQRS detection from single-channel NI-fECG signals, without cancelling out the mECG. The proposed method leverages the different spectral behaviour exhibited by mECG and fECG signals. Fetal R-peaks are detected using a hybrid combination of k-means clustering with time and time-frequency features extracted from pre-processed NI-fECG recordings. The performance of our method is evaluated using real and synthetic signals from publicly available datasets, achieving a best of 96.3% sensitivity and 90.4% F1 score. The results obtained demonstrates the effectiveness of the proposed method for the detection of fQRS complexes with high sensitivity and low computational complexity.

Monitoring the fetal heart rate (FHR) is common practice in obstetric care to assess the risk of fetal compromise. Unfortunately, human interpretation of FHR recordings is subject to inter-observer variability with high false positive rates. To improve the performance of fetal compromise detection, deep learning methods have been proposed to automatically interpret FHR recordings. However, existing deep learning methods typically analyse a fixed-length segment of the FHR recording after removing signal gaps, where the influence of this segment selection process has not been comprehensively assessed. In this work, we develop a novel input length invariant deep learning model to determine the effect of FHR segment selection for detecting fetal compromise. Using this model, we perform five times repeated five-fold cross-validation on an open-access database of 552 FHR recordings and assess model performance for FHR segment lengths between 15 and 60 minutes. We show that the performance after removing signal gaps improves with increasing segment length from 15 minutes (AUC = 0.50) to 60 minutes (AUC = 0.74). Additionally, we demonstrate that using FHR segments without removing signal gaps achieves superior performance across signal lengths from 15 minutes (AUC = 0.68) to 60 minutes (AUC = 0.76). These results show that future works should carefully consider FHR segment selection and that removing signal gaps might contribute to the loss of valuable information.

The independent component analysis (ICA) based methods are among the most prevalent techniques used for non-invasive fetal electrocardiogram (NI-fECG) processing. Often, these methods are combined with other methods, such adaptive algorithms. However, there are many variants of the ICA methods and it is not clear which one is the most suitable for this task. The goal of this study is to test and objectively evaluate 11 variants of ICA methods combined with an adaptive fast transversal filter (FTF) for the purpose of extracting the NI-fECG. The methods were tested on two datasets, Labour dataset and Pregnancy dataset, which contained real records obtained during clinical practice. The efficiency of the methods was evaluated from the perspective of determining the accuracy of detection of QRS complexes through the parameters of accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and harmonic mean between SE and PPV (F1). The best results were achieved with a combination of FastICA and FTF, which yielded mean values of ACC = 83.72%, SE = 92.13%, PPV = 90.16%, and F1 = 91.14%. Time of calculation was also taken into consideration in the methods. Although FastICA was ranked to be the sixth fastest with its mean computation time of 0.452 s, it had the best ratio of performance and speed. The combination of FastICA and adaptive FTF filter turned out to be very promising. In addition, such device would require signals acquired from the abdominal area only; no need to acquire reference signal from the mother's chest., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Jaros et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)