Monitoring uterine activity during labor: a comparison of 3 methods

Fetal Heart Rate Preprocessing Techniques: A Scoping Review

Monitoring fetal heart rate (FHR) through cardiotocography is crucial for the early diagnosis of fetal distress situations, necessitating prompt obstetrical intervention. However, FHR signals are often marred by various contaminants, making preprocessing techniques essential for accurate analysis. This scoping review, following PRISMA-ScR guidelines, describes the preprocessing methods in original research articles on human FHR (or beat-to-beat intervals) signal preprocessing from PubMed and Web of Science, published from their inception up to May 2021. From the 322 unique articles identified, 54 were included, from which prevalent preprocessing approaches were identified, primarily focusing on the detection and correction of poor signal quality events. Detection usually entailed analyzing deviations from neighboring samples, whereas correction often relied on interpolation techniques. It was also noted that there is a lack of consensus regarding the definition of missing samples, outliers, and artifacts. Trends indicate a surge in research interest in the decade 2011-2021. This review underscores the need for standardizing FHR signal preprocessing techniques to enhance diagnostic accuracy. Future work should focus on applying and evaluating these methods across FHR databases aiming to assess their effectiveness and propose improvements.

Multi-channel electrohysterography enabled uterine contraction characterization and its effect in delivery assessment

Uterine contractions are routinely monitored by tocodynamometer (TOCO) at late stage of pregnancy to predict the onset of labor. However, TOCO reveals no information on the synchrony and coherence of contractions, which are important contributors to a successful delivery. The electrohysterography (EHG) is a recording of the electrical activities that trigger the local muscles to contract. The spatial-temporal information embedded in multiple channel EHG signals make them ideal for characterizing the synchrony and coherence of uterine contraction. To proceed, contractile time-windows are identified from TOCO signals and are then used to segment out the simultaneously recorded EHG signals of different channels. We construct sample entropy SamEn and Concordance Correlation based feature ψ from these EHG segments to quantify the synchrony and coherence of contraction. To test the effectiveness of the proposed method, 122 EHG recordings in the Icelandic EHG database were divided into two groups according to the time difference between the gestational ages at recording and at delivery (TTD). Both SamEn and ψ show clear difference in the two groups (p<10-5) even when measurements were made 120 h before delivery. Receiver operating characteristic curve analysis of these two features gave AUC values of 0.834 and 0.726 for discriminating imminent labor defined with TTD ≤ 24 h. The SamEn was significantly smaller in women (0.1433) of imminent labor group than in women (0.3774) of the pregnancy group. Using an optimal cutoff value of SamEn to identify imminent labor gives sensitivity, specificity, and accuracy as high as 0.909, 0.712 and 0.743, respectively. These results demonstrate superiority in comparing to the existing SOTA methods. This study is the first research work focusing on characterizing the synchrony property of contractions from the electrohysterography signals. Despite the very limited dataset used in the validation process, the promising results open a new direction to the use of electrohysterography in obstetrics.

Computerised Cardiotocography Analysis for the Automated Detection of Fetal Compromise during Labour: A Review

The measurement and analysis of fetal heart rate (FHR) and uterine contraction (UC) patterns, known as cardiotocography (CTG), is a key technology for detecting fetal compromise during labour. This technology is commonly used by clinicians to make decisions on the mode of delivery to minimise adverse outcomes. A range of computerised CTG analysis techniques have been proposed to overcome the limitations of manual clinician interpretation. While these automated techniques can potentially improve patient outcomes, their adoption into clinical practice remains limited. This review provides an overview of current FHR and UC monitoring technologies, public and private CTG datasets, pre-processing steps, and classification algorithms used in automated approaches for fetal compromise detection. It aims to highlight challenges inhibiting the translation of automated CTG analysis methods from research to clinical application and provide recommendations to overcome them.

Prediction of Preterm Labor from the Electrohysterogram Signals Based on Different Gestational Weeks

Timely preterm labor prediction plays an important role for increasing the chance of neonate survival, the mother's mental health, and reducing financial burdens imposed on the family. The objective of this study is to propose a method for the reliable prediction of preterm labor from the electrohysterogram (EHG) signals based on different pregnancy weeks. In this paper, EHG signals recorded from 300 subjects were split into 2 groups: (I) those with preterm and term labor EHG data that were recorded prior to the 26th week of pregnancy (referred to as the PE-TE group), and (II) those with preterm and term labor EHG data that were recorded after the 26th week of pregnancy (referred to as the PL-TL group). After decomposing each EHG signal into four intrinsic mode functions (IMFs) by empirical mode decomposition (EMD), several linear and nonlinear features were extracted. Then, a self-adaptive synthetic over-sampling method was used to balance the feature vector for each group. Finally, a feature selection method was performed and the prominent ones were fed to different classifiers for discriminating between term and preterm labor. For both groups, the AdaBoost classifier achieved the best results with a mean accuracy, sensitivity, specificity, and area under the curve (AUC) of 95%, 92%, 97%, and 0.99 for the PE-TE group and a mean accuracy, sensitivity, specificity, and AUC of 93%, 90%, 94%, and 0.98 for the PL-TL group. The similarity between the obtained results indicates the feasibility of the proposed method for the prediction of preterm labor based on different pregnancy weeks.

Assessment of uterine contractions in labor and delivery

Normal labor and delivery are dependent on the presence of regular and effective contractions of the uterine myometrium. The mechanisms responsible for the initiation and maintenance of adequate and synchronized uterine activity that are necessary for labor and delivery result from a complex interplay of hormonal, mechanical, and electrical factors that have not yet been fully elucidated. Monitoring uterine activity during term labor and in suspected preterm labor is an important component of obstetrical care because cases of inadequate and excessive uterine activity can be associated with substantial maternal and neonatal morbidity and mortality. Inadequate labor progress is a common challenge encountered in intrapartum care, with labor dystocia being the most common indication for cesarean deliveries performed during labor. Hereafter, an accurate assessment of uterine activity during labor can assist in the management of protracted labor by diagnosing inadequate uterine activity and facilitating the titration of uterotonic medications before a trial of labor is prematurely terminated. Conversely, the ability to diagnose unwanted or excessive uterine activity is also critical in cases of threatened preterm labor, tachysystole, or patients undergoing a trial of labor after cesarean delivery. Knowledge of uterine activity in these cases may guide the use of tocolytic medications or raise suspicion of uterine rupture. Current diagnostic capabilities are less than optimal, hindering the medical management of term and preterm labor. Currently, different methods exist for evaluating uterine activity during labor, including manual palpation, external tocodynamometry, intrauterine pressure monitoring, and electrical uterine myometrial activity tracing. Legacy uterine monitoring techniques have advantages and limitations. External tocodynamometry is the most widespread tool in clinical use owing to its noninvasive nature and its ability to time contractions against the fetal heart rate monitor. However, it does not provide information regarding the strength of uterine contractions and is limited by signal loss with maternal movements. Conversely, the intrauterine pressure catheter quantifies the strength of uterine contractions; however, its use is limited by its invasiveness, risk for complications, and limited additive value in all but few clinical scenarios. New monitoring methods are being used, such as electrical uterine monitoring, which is noninvasive and does not require ruptured membranes. Electrical uterine monitoring has yet to be incorporated into common clinical practice because of lack of access to this technology, its high cost, and the need for appropriate training of clinical staff. Further work needs to be done to increase the accessibility and implementation of this technique by experts, and further research is needed to implement new practical and useful methods. This review describes current clinical tools for uterine activity assessment during labor and discusses their advantages and shortcomings. The review also summarizes current knowledge regarding novel technologies for monitoring uterine contractions that are not yet in widespread use, but are promising and could help improve our understanding of the physiology of labor, delivery, and preterm labor, and ultimately enhance patient care.

Quantitative analysis for grading uterine electromyography activities during labor

BACKGROUND

The strength of uterine contraction is one of the decisive factors for labor progression and parturition. Clinicians usually encounter difficulties in early identification of inadequate contractions and in oxytocin treatment. Electromyography-an emerging technology for uterine contraction monitoring-can quantify the intensity of myoelectric activity of uterine contraction. Therefore, grading patients with different uterine contraction intensities by electromyography is of great significance to the clinical intensive management of uterine contraction and labor process.

OBJECTIVE

This study aimed to quantify and grade electromyography activity during the latent phase of the first stage of labor and explore its relationship with oxytocin treatment and length of labor.

STUDY DESIGN

We performed a retrospective cohort study to identify electromyography parameters as a predictor for oxytocin treatment and length of labor among a cohort of term singleton primipara (n=508) during the latent phase who delivered in Guangzhou between August 2018 and December 2021. The electromyography parameters were graded according to the quartile method, and the significance of grading and delivery outcome was explored. Univariate and multivariate logistic regression were used to determine the predictors of oxytocin treatment.

RESULTS

Maternal gestational age (adjusted risk ratio, 1.2; 95% confidence interval, 1.0-1.5), root mean square (adjusted risk ratio, 0.01; 95% confidence interval, 0.004-0.03), and power (adjusted risk ratio, 0.02; 95% confidence interval, 0.01-0.05) were significant predictors of oxytocin argumentation. The low electromyography activity group had a longer first stage labor and total labor time and were more likely to use oxytocin.

CONCLUSION

Electromyography parameters root mean square and power had high predictive values for later oxytocin treatment among patients with spontaneous labor. Patients with low-grade electromyography were more likely need oxytocin treatment. Electromyography grading is very important for its clinical promotion and use, and it could lead to more reliable analyses of oxytocin treatments and eventually to more effective interventions to prevent prolonged labor.

Beat-to-beat fetal heart rate analysis using portable medical device and wavelet transformation technique

Objective: Beat-to-beat tele-fetal monitoring and comparison with clinical data are studied with a wavelet transformation approach. Tele-fetal monitoring is a big progress toward a wearable medical device for pregnant women capable of obtaining prenatal care at home. Study Design: We apply a wavelet transformation algorithm for fetal cardiac monitoring using a portable fetal Doppler medical device. After an investigation of 85 different mother wavelets, a bio-orthogonal 2.2 mother wavelet in level 4 of decomposition is chosen. The efficiency of the proposed method is evaluated using two data sets including public and clinical. Results: From publicly available data on PhysioBank, and simultaneous clinical measurement, we prove that the comparison between obtained fetal heart rate by the algorithm and the baselines yields a promising accuracy beyond 95%. Conclusion: Finally, we conclude that the proposed algorithm would be a robust technique for any similar tele-fetal monitoring approach.

Comparison of Oxytocin vs. Carbetocin Uterotonic Activity after Caesarean Delivery Assessed by Electrohysterography: A Randomised Trial

Electrohysterography has been used for monitoring uterine contractility in pregnancy and labour. Effective uterine contractility is crucial for preventing postpartum haemorrhage. The objective of our study was to compare postpartum electrohysterograms in women receiving oxytocin vs. carbetocin for postpartum haemorrhage prevention after caesarean delivery. The trial is registered at ClinicalTrials.gov with the identifier NCT04201665. We included 64 healthy women with uncomplicated singleton pregnancies at term scheduled for caesarean section after one previous caesarean section. After surgery, a 15 min electrohysterogram was obtained after which women were randomised to receive either five IU of oxytocin intravenously or 100 μg of carbetocin intramuscularly. A 30 min electrohysterogram was performed two hours after drug application. Changes in power density spectrum peak frequency of electrohysterogram pseudo-bursts were analysed. A significant reduction in power density spectrum peak frequency in the first two hours was observed after carbetocin but not after oxytocin (median = 0.07 (interquartile range (IQR): 0.87 Hz) compared to median = -0.63 (IQR: 0.20) Hz; p = 0.004). Electrohysterography can be used for objective comparison of uterotonic effects. We found significantly higher power density spectrum peak frequency two hours after oxytocin compared to carbetocin.

A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device

Background: Uterine activity (UA) monitoring is an essential element of pregnancy management. The gold-standard intrauterine pressure catheter (IUPC) is invasive and requires ruptured membranes, while the standard-of-care, external tocodynamometry (TOCO)’s accuracy is hampered by obesity, maternal movements, and belt positioning. There is an urgent need to develop telehealth tools enabling patients to remotely access care. Here, we describe and demonstrate a novel algorithm enabling remote, non-invasive detection and monitoring of UA by analyzing the modulation of the maternal electrocardiographic and phonocardiographic signals. The algorithm was designed and implemented as part of a wireless, FDA-cleared device designed for remote pregnancy monitoring. Two separate prospective, comparative, open-label, multi-center studies were conducted to test this algorithm.

Methods: In the intrapartum study, 41 laboring women were simultaneously monitored with IUPC and the remote pregnancy monitoring device. Ten patients were also monitored with TOCO. In the antepartum study, 147 pregnant women were simultaneously monitored with TOCO and the remote pregnancy monitoring device.

Results: In the intrapartum study, the remote pregnancy monitoring device and TOCO had sensitivities of 89.8 and 38.5%, respectively, and false discovery rates (FDRs) of 8.6 and 1.9%, respectively. In the antepartum study, a direct comparison of the remote pregnancy monitoring device to TOCO yielded a sensitivity of 94% and FDR of 31.1%. This high FDR is likely related to the low sensitivity of TOCO.

Conclusion: UA monitoring via the new algorithm embedded in the remote pregnancy monitoring device is accurate and reliable and more precise than TOCO standard of care. Together with the previously reported remote fetal heart rate monitoring capabilities, this novel method for UA detection expands the remote pregnancy monitoring device’s capabilities to include surveillance, such as non-stress tests, greatly benefiting women and providers seeking telehealth solutions for pregnancy care.

Assessment of Features between Multichannel Electrohysterogram for Differentiation of Labors

Electrohysterogram (EHG) is a promising method for noninvasive monitoring of uterine electrical activity. The main purpose of this study was to characterize the multichannel EHG signals to distinguish between term delivery and preterm birth, as well as deliveries within and beyond 24 h. A total of 219 pregnant women were grouped in two ways: (1) term delivery (TD), threatened preterm labor (TPL) with the outcome of preterm birth (TPL_PB), and TPL with the outcome of term delivery (TPL_TD); (2) EHG recording time to delivery (TTD) ≤ 24 h and TTD > 24 h. Three bipolar EHG signals were analyzed for the 30 min recording. Six EHG features between multiple channels, including multivariate sample entropy, mutual information, correlation coefficient, coherence, direct partial Granger causality, and direct transfer entropy, were extracted to characterize the coupling and information flow between channels. Significant differences were found for these six features between TPL and TD, and between TTD ≤ 24 h and TTD > 24 h. No significant difference was found between TPL_PB and TPL_TD. The results indicated that EHG signals of TD were more regular and synchronized than TPL, and stronger coupling between multichannel EHG signals was exhibited as delivery approaches. In addition, EHG signals propagate downward for the majority of pregnant women regardless of different labors. In conclusion, the coupling and propagation features extracted from multichannel EHG signals could be used to differentiate term delivery and preterm birth and may predict delivery within and beyond 24 h.

Novel uterine contraction monitoring to enable remote, self-administered nonstress testing

BACKGROUND

The serial fetal monitoring recommended for women with high-risk pregnancies places a substantial burden on the patient, often disproportionately affecting underprivileged and rural populations. A telehealth solution that can empower pregnant women to obtain recommended fetal surveillance from the comfort of their own home has the potential to promote health equity and improve outcomes. We have previously validated a novel, wireless pregnancy monitor that can remotely capture fetal and maternal heart rates. However, such a device must also detect uterine contractions if it is to be used to robustly conduct remote nonstress tests.

OBJECTIVE

This study aimed to describe and validate a novel algorithm that uses biopotential and acoustic signals to noninvasively detect uterine contractions via a wireless pregnancy monitor.

STUDY DESIGN

A prospective, open-label, 2-center study evaluated simultaneous detection of uterine contractions by the wireless pregnancy monitor and an intrauterine pressure catheter in women carrying singleton pregnancies at ≥32 0/7 weeks' gestation who were in the first stage of labor (ClinicalTrials.gov Identifier: NCT03889405). The study consisted of a training phase and a validation phase. Simultaneous recordings from each device were passively acquired for 30 to 60 minutes. In a subset of the monitoring sessions in the validation phase, tocodynamometry was also deployed. Three maternal-fetal medicine specialists, blinded to the data source, identified and marked contractions in all modalities. The positive agreement and false-positive rates of both the wireless monitor and tocodynamometry were calculated and compared with that of the intrauterine pressure catheter.

RESULTS

A total of 118 participants were included, 40 in the training phase and 78 in the validation phase (of which 39 of 78 participants were monitored simultaneously by all 3 devices) at a mean gestational age of 38.6 weeks. In the training phase, the positive agreement for the wireless monitor was 88.4% (1440 of 1692 contractions), with a false-positive rate of 15.3% (260/1700). In the validation phase, using the refined and finalized algorithm, the positive agreement for the wireless pregnancy monitor was 84.8% (2722/3210), with a false-positive rate of 24.8% (897/3619). For the subgroup who were monitored only with the wireless monitor and intrauterine pressure catheter, the positive agreement was 89.0% (1191/1338), with a similar false-positive rate of 25.4% (406/1597). For the subgroup monitored by all 3 devices, the positive agreement for the wireless monitor was significantly better than for tocodynamometry (P<.0001), whereas the false-positive rate was significantly higher (P<.0001). Unlike tocodynamometry, whose positive agreement was significantly reduced in the group with obesity compared with the group with normal weight (P=.024), the positive agreement of the wireless monitor did not vary across the body mass index groups.

CONCLUSION

This novel method to noninvasively monitor uterine activity, via a wireless pregnancy monitoring device designed for self-administration at home, was more accurate than the commonly used tocodynamometry and unaffected by body mass index. Together with the previously reported remote fetal heart rate monitoring capabilities, this added ability to detect uterine contractions has created a complete telehealth solution for remote administration of nonstress tests.

A Preliminary Exploration of the Placental Position Influence on Uterine Electromyography Using Fractional Modelling

The uterine electromyogram, also called electrohysterogram (EHG), is the electrical signal generated by uterine contractile activity. The EHG has been considered an expanding technique for pregnancy monitoring and preterm risk evaluation. Data were collected on the abdominal surface. It has been speculated the effect of the placenta location on the characteristics of the EHG. In this work, a preliminary exploration method is proposed using the average spectra of Alvarez waves contractions of subjects with anterior and non-anterior placental position as a basis for the triple-dispersion Cole model that provides a best fit for these two cases. This leads to the uterine impedance estimation for these two study cases. Non-linear least square fitting (NLSF) was applied for this modelling process, which produces electric circuit fractional models’ representations. A triple-dispersion Cole-impedance model was used to obtain the uterine impedance curve in a frequency band between 0.1 and 1 Hz. A proposal for the interpretation relating the model parameters and the placental influence on the myometrial contractile action is provided. This is the first report regarding in silico estimation of the uterine impedance for cases involving anterior or non-anterior placental positions.

Prediction of Preterm Delivery from Unbalanced EHG Database

Objective: The early prediction of preterm labor can significantly minimize premature delivery complications for both the mother and infant. The aim of this research is to propose an automatic algorithm for the prediction of preterm labor using a single electrohysterogram (EHG) signal. Method: The proposed method firstly employs empirical mode decomposition (EMD) to split the EHG signal into two intrinsic mode functions (IMFs), then extracts sample entropy (SampEn), the root mean square (RMS), and the mean Teager–Kaiser energy (MTKE) from each IMF to form the feature vector. Finally, the extracted features are fed to a k-nearest neighbors (kNN), support vector machine (SVM), and decision tree (DT) classifiers to predict whether the recorded EHG signal refers to the preterm case. Main results: The studied database consists of 262 term and 38 preterm delivery pregnancies, each with three EHG channels, recorded for 30 min. The SVM with a polynomial kernel achieved the best result, with an average sensitivity of 99.5%, a specificity of 99.7%, and an accuracy of 99.7%. This was followed by DT, with a mean sensitivity of 100%, a specificity of 98.4%, and an accuracy of 98.7%. Significance: The main superiority of the proposed method over the state-of-the-art algorithms that studied the same database is the use of only a single EHG channel without using either synthetic data generation or feature ranking algorithms.

The relationship of myometrial histopathology (metropathy) to myometrial dysfunction and clinical manifestations

Myometrial morphology and myometrial physiology have been considered to be separate entities; however, observations of myometrial morphology and associated dysfunctions suggest a relationship between myometrial morphology and myometrial physiology that deserves further exploration. Although myometrial electrical activity can be monitored by electrohysterogram, the association of increased myometrial contractions with an increase in electrical activity (due to an increase in gap junctions) is typically not evaluated. Although the association of increased myometrial contractions with increase in pain can be monitored by tocometry and intrauterine pressure catheters, respectively, this is generally not done in the non-pregnant uteri. Although standard morphologic evaluations routinely include evaluation with special stains and immunohistochemistry in other organ systems, such as skeletal and cardiac muscle, these evaluations are not standard or routine for myometrium in hysterectomies. The purpose of this review is to discuss non-neoplastic myometrial histology, with consideration of the potential value of using tools to measure variations in myometrial physiology, in order to reliably correlate myometrial histology with myometrial function (and dysfunction).

Network theory based EHG signal analysis and its application in preterm prediction

OBJECTIVE

Preterm birth is the leading cause of neonatal morbidity and mortality. Early identification of high-risk patients followed by medical interventions is essential to the prevention of preterm birth. Based on the relationship between uterine contraction and the fundamental electrical activities of muscles, we extracted effective features from EHG signals recorded from pregnant women, and use them to train classifiers with the purpose of providing high precision in classifying term and preterm pregnancies.

METHODS

To characterize changes from irregularity to coherence of the uterine activity during the whole pregnancy, network representations of the original electrohysterogram (EHG) signals are established by applying the Horizontal Visibility Graph (HVG) algorithm, from which we extract network degree density and distribution, clustering coefficient and assortativity coefficient. Concerns on the interferences of different noise sources embedded in the EHG signal, we apply Short-Time Fourier Transform (STFT) to expand the original signal in the time-frequency domain. This allows a network representation and the extraction of related features on each frequency component. Feature selection algorithms are then used to filter out unrelated frequency components. We further apply the proposed feature extraction method to EHG signals available in the Term-Preterm EHG database (TPEHG), and use them to train classifiers. We adopt the Partition-Synthesis scheme which splits the original imbalanced dataset into two sets and synthesizes artificial samples separately within each subset to solve the problem of dataset imbalance.

RESULTS

The optimally selected network-based features, not only contribute to the identification of the essential frequency components of uterine activities related to preterm birth, but also to improved performance in classifying term/preterm pregnancies, i.e., the SVM (Support Vector Machine) classifier trained with the available samples in the TPEHG gives sensitivity, specificity, overall accuracy, and auc values as high as 0.89, 0.93, 0.91, and 0.97, respectively.

Association between Increased Uterine Activity, as Recorded Noninvasively from the Anterior Abdominal Wall at 34 Weeks' Gestation, and Preterm Birth

Background

There is a need to accurately identify pregnant women at risk for preterm birth as early as possible. Recent developments in technology enable the recording of uterine electrical activity (electrohysterogram) from the anterior abdominal wall in a non-invasive way.

Objective

To investigate whether uterine activity recorded under resting conditions at a gestational age of 34 weeks could identify a risk of preterm birth.

Study design

A commercial antenatal holter device with its dedicated software was used to record and store raw data of the maternal and fetal electrocardiograms and uterine activity for the Safe Passage Study. Uterine activity was recorded under resting conditions from 34 weeks' gestation in epochs of 250 ms (millisecond) for at least 30 min. From this database the raw data, recorded at a mean gestational age of 34 weeks, of 50 women who had preterm deliveries were selected for comparison with data of women who had term deliveries. Mean uterine activity, expressed in microvolt (μV)/epoch, was used for the comparison.

Results

After exclusion of 25 participants where labour was induced or augmented and another three for other reasons, 36 remained in each group. The participants in each group were comparable in respect of maternal age, gravidity, parity, gestational age at recruitment and duration of recording. Uterine activity in the preterm group (60.3 μV/epoch) differed significantly (p<0.01) from that of the comparison group (52.4 μV/epoch). Using a cut-off point of 52.3 μV/epoch as obtained from receiver operator characteristic curves (area under the curve 0.72), the sensitivity and specificity of identifying risks of preterm labour were 81% and 50% respectively.

Conclusion

Results of this small study are promising but need to be confirmed in larger studies and preferably at earlier gestational age.

Identification of Contractions from Electrohysterography for Prediction of Prolonged Labor

The analysis of the uterine electrical activity and its propagation patterns could potentially predict the risk of prolonged/arrested progress of labor. In our study, the Electrohysterography (EHG) signals of 83 participants in labor at around 3-4 cm of cervical dilatation, were recorded for about 30 minutes each. These signals were analyzed for predicting prolonged labor. Out of the 83 participants, 70 participants had normal progress of labor and delivered vaginally. The remaining 13 participants had prolonged/ arrested progress of labor and had to deliver through a cesarean section. In this paper, we propose an algorithm to identify contractions from the acquired EHG signals based on the energy of the signals. The role of contraction consistency and fundal dominance was evaluated for impact on progress of the labor. As per our study, the correlation of contractions was higher in case of normal progress of labor. We also observed that the upper uterine segment was dominant in cases with prolonged/arrested progress of labor.

Assessment of Dispersion and Bubble Entropy Measures for Enhancing Preterm Birth Prediction Based on Electrohysterographic Signals

One of the remaining challenges for the scientific-technical community is predicting preterm births, for which electrohysterography (EHG) has emerged as a highly sensitive prediction technique. Sample and fuzzy entropy have been used to characterize EHG signals, although they require optimizing many internal parameters. Both bubble entropy, which only requires one internal parameter, and dispersion entropy, which can detect any changes in frequency and amplitude, have been proposed to characterize biomedical signals. In this work, we attempted to determine the clinical value of these entropy measures for predicting preterm birth by analyzing their discriminatory capacity as an individual feature and their complementarity to other EHG characteristics by developing six prediction models using obstetrical data, linear and non-linear EHG features, and linear discriminant analysis using a genetic algorithm to select the features. Both dispersion and bubble entropy better discriminated between the preterm and term groups than sample, spectral, and fuzzy entropy. Entropy metrics provided complementary information to linear features, and indeed, the improvement in model performance by including other non-linear features was negligible. The best model performance obtained an F1-score of 90.1 ± 2% for testing the dataset. This model can easily be adapted to real-time applications, thereby contributing to the transferability of the EHG technique to clinical practice.

Advanced Bioelectrical Signal Processing Methods: Past, Present, and Future Approach-Part III: Other Biosignals

Analysis of biomedical signals is a very challenging task involving implementation of various advanced signal processing methods. This area is rapidly developing. This paper is a Part III paper, where the most popular and efficient digital signal processing methods are presented. This paper covers the following bioelectrical signals and their processing methods: electromyography (EMG), electroneurography (ENG), electrogastrography (EGG), electrooculography (EOG), electroretinography (ERG), and electrohysterography (EHG).

A novel algorithm based on ensemble empirical mode decomposition for non-invasive fetal ECG extraction

Non-invasive fetal electrocardiography appears to be one of the most promising fetal monitoring techniques during pregnancy and delivery nowadays. This method is based on recording electrical potentials produced by the fetal heart from the surface of the maternal abdomen. Unfortunately, in addition to the useful fetal electrocardiographic signal, there are other interference signals in the abdominal recording that need to be filtered. The biggest challenge in designing filtration methods is the suppression of the maternal electrocardiographic signal. This study focuses on the extraction of fetal electrocardiographic signal from abdominal recordings using a combination of independent component analysis, recursive least squares, and ensemble empirical mode decomposition. The method was tested on two databases, the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations and the PhysioNet Challenge 2013 database. The evaluation was performed by the assessment of the accuracy of fetal QRS complexes detection and the quality of fetal heart rate determination. The effectiveness of the method was measured by means of the statistical parameters as accuracy, sensitivity, positive predictive value, and F1-score. Using the proposed method, when testing on the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations database, accuracy higher than 80% was achieved for 11 out of 12 recordings with an average value of accuracy 92.75% [95% confidence interval: 91.19-93.88%], sensitivity 95.09% [95% confidence interval: 93.68-96.03%], positive predictive value 96.36% [95% confidence interval: 95.05-97.17%] and F1-score 95.69% [95% confidence interval: 94.83-96.35%]. When testing on the Physionet Challenge 2013 database, accuracy higher than 80% was achieved for 17 out of 25 recordings with an average value of accuracy 78.24% [95% confidence interval: 73.44-81.85%], sensitivity 81.79% [95% confidence interval: 76.59-85.43%], positive predictive value 87.16% [95% confidence interval: 81.95-90.35%] and F1-score 84.08% [95% confidence interval: 80.75-86.64%]. Moreover, the non-invasive ST segment analysis was carried out on the records from the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations database and achieved high accuracy in 7 from in total of 12 records (mean values μ < 0.1 and values of ±1.96σ < 0.1).

Alvarez waves in pregnancy: a comprehensive review

Alvarez waves are local rhythmic contractions of the myometrium with high frequency and low intensity. They can be detected using internal or external tocography and electrohysterography. Some researchers correlate these small contractions with the initiation of labor, since they have been described as a pattern representing the uterine response to prostaglandin production. Other authors either do not validate a causality relation between Alvarez waves and labor or suggest that they have low predictive value for preterm labor. Alvarez waves' research has become a multidisciplinary subject with inputs ranging from medical science, biomedical engineering, and related areas. A comprehensive review is herein conducted to summarize the state of the art regarding Alvarez waves and their role in the initiation of labor, namely in preterm birth. The results show that a large number of studies have analyzed and characterized Alvarez waves without necessarily digging into their relationship with labor. Publications were categorized in three groups: (A) reports about morphology and characterization of Alvarez waves; (B) publications reporting a positive causality relation between Alvarez waves and labor; and (C) publications reporting an absence of causality regarding the previous hypothesis. Studies in group B outnumbered those in group C. A critical analysis is presented.

A study of uterine inertia on the spontaneous of labor using uterine electromyography

OBJECTIVE

The purpose of this study is to analyze uterine electromyography burst patterns in patients with spontaneous labor and patients with uterine inertia.

MATERIALS AND METHODS

Uterine electromyography was recorded using 4 silver/silver chloride electrodes placed periumbilical. Thirty women in the spontaneous labor were enrolled. Uterine electromyography was also recorded from patients with uterine inertia before and after oxytocin treatment. EMG bursts were characterized by analysis of multiple variables including burst frequency, duration, root mean squared, amplitude, and total power.

RESULTS

There were significant reductions (P < .01) in all EMG burst characteristics. In addition, uterine electromyography parameters were all increased after oxytocin treatment and were comparable (P > .05) to patients in spontaneous labor.

CONCLUSIONS

Uterine electromyography can be used effectively to distinguish patients progressing with spontaneous labor from patients that develop uterine inertia. Uterine inertia is characterized by reduced EMG activity and failure of cervical dilation. Uterine electromyography is a quantitative, non-invasive assessment tool that contributes to the diagnosis, evaluation and management of patients with spontaneous labor and uterine inertia.

Noninvasive monitoring of uterine electrical activity among patients with obesity: a new external monitoring device

BACKGROUND

Tocodynamometry is a common, noninvasive tool used to measure contraction frequency; however, its utility is often limited in patients with obesity. An intrauterine pressure catheter provides a more accurate measurement of uterine contractions but requires ruptured membranes, limiting its utility during early latent labor. Electrical uterine myography has shown promise as a noninvasive contraction monitor with efficacy similar to that of the intrauterine pressure catheter; however, its efficacy has not been widely studied in the obese population.

OBJECTIVE

This study aimed to validate the accuracy of electrical uterine myography by comparing it with tocodynamometry and intrauterine pressure catheters among laboring patients with obesity.

STUDY DESIGN

This was a prospective observational study from February 2017 to April 2018 of patients with obesity, aged 18 years or older, who were admitted to the labor unit with viable singleton pregnancies and no contraindications for electromyography. Patients were monitored simultaneously with electrical myography and tocodynamometry or intrauterine catheter for more than 30 minutes. Two blinded obstetricians reviewed the tracings. The outcomes of interest were continuous and interpretable tracing, number of contractions, and timing and duration of contractions, interpreted as point estimates and associated 95% confidence intervals.

RESULTS

A total of 110 patients were enrolled (65 tocodynamometry, 55 intrauterine catheter). Electrical myography was significantly more interpretable during a 30-minute tracing (P=.001) and detected 39% more contractions than tocodynamometry (P<.0001; 95% confidence interval, 23%-57%), whereas there was no difference in the interpretability of tracings or number of contractions between electrical myography and an intrauterine catheter (P=.16; 95% confidence interval, -0.19 to 1.19). Patients who underwent simultaneous monitoring preferred the electrical myography device over tocodynamometry.

CONCLUSION

Electrical uterine myography is superior to tocodynamometry in the detection of intrapartum uterine contraction monitoring and comparable with internal contraction monitoring.

Clinical evaluation of electrohysterography as method of monitoring uterine contractions during labor: A propensity score matched study

OBJECTIVE

Electrohysterography is a non-invasive technique to monitor uterine activity and has a significantly higher sensitivity compared to conventional external tocodynamometry. Whether this technique could lead to improved obstetrical outcomes is still unknown. In this propensity score matched study, clinical results of the first pilot implementing electrohysterography during labor were evaluated. The hypothesis tested is that electrohysterography will help to optimize uterine activity and thereby lead to fewer obstetric interventions. Secondary outcomes were Apgar score, arterial umbilical pH values, first stage labor duration, episiotomy rate and postpartum vaginal blood loss.

STUDY DESIGN

From November 2017 until October 2018, electrohysterography was introduced as a standard alternative for monitoring uterine activity in high-risk deliveries. It could be applied in case of induced labor, previous cesarean delivery, body mass index ≥30 kg/m² or an inadequate external tocodynamometry monitoring. Outcomes were compared to a matched group of women in which external tocodynamometry was applied for uterine activity monitoring during labor. These women were identified using propensity scores.

RESULTS

A total of 348 women received electrohysterography as standard method of uterine monitoring during labor. A match (1:1 ratio) was found for 317 women, resulting in a total population of 634 women. No significant differences were seen in obstetric interventions (i.e. cesarean deliveries and assisted vaginal deliveries) between the electrohysterography and tocodynamometry group (P = 0.80). No statistically significant differences were seen regarding the secondary outcomes.

CONCLUSIONS

This first pilot study implementing electrohysterography as monitoring method during labor in a high-risk population did not result in statistically significant differences regarding obstetric interventions, low Apgar scores or low umbilical artery pH values. Therefore, we suggest that electrohysterography causes no harm and we recommend further implementation and evaluation in clinical practice.

Differentiation of fluctuations in uterine contractions associated with Term pregnancies using adaptive fractal features of electromyography signals

Analysis of uterine contractions using electromyography signals is gaining importance due to its capability to measure the dynamics of uterus. Uterine electromyography (uEMG) provides information on the nature of uterine contractions non-invasively. In this study, the fluctuations in uEMG signals associated with Term pregnancies are analyzed. For this, Term uEMG signals corresponding to second (T1) and third (T2) trimesters are considered. The signals are subjected to Adaptive Fractal Analysis (AFA), wherein a global trend is obtained by using overlapping windows of three orders namely, 25%, 50% and 75%. The signals are detrended and the fluctuation function is estimated. Two Hurst exponent features computed at short range (Hs) and long range (Hl) are extracted and statistically analyzed. Results show that AFA is able to characterize variations in the fluctuations of Term delivery signals. The feature values are observed to vary significantly during different weeks of gestation. It is found that features of T2 signals are higher than that of T1 signals for all the considered overlaps, indicating that T2 signals possess smoother characteristics than T1 signals. Further, coefficient of variation is observed to be low, indicating that these features are able to handle the inter-subject variations in Term signals. Therefore, it appears that the proposed approach could aid in investigation of progressive changes in uterine contractions during Term pregnancies.

Automatic recognition of uterine contractions with electrohysterogram signals based on the zero-crossing rate

Uterine contraction (UC) is an essential clinical indicator in the progress of labour and delivery. Electrohysterogram (EHG) signals recorded on the abdomen of pregnant women reflect the uterine electrical activity. This study proposes a novel algorithm for automatic recognition of UCs with EHG signals to improve the accuracy of detecting UCs. EHG signals by electrodes, the tension of the abdominal wall by tocodynamometry (TOCO) and maternal perception were recorded simultaneously in 54 pregnant women. The zero-crossing rate (ZCR) of the EHG signal and its power were calculated to modulate the raw EHG signal and highlight the EHG bursts. Then the envelope was extracted from the modulated EHG for UC recognition. Besides, UC was also detected by the conventional TOCO signal. Taking maternal perception as a reference, the UCs recognized by EHG and TOCO were evaluated with the sensitivity, positive predictive value (PPV), and UC parameters. The results show that the sensitivity and PPV are 87.8% and 93.18% for EHG, and 84.04% and 90.89% for TOCO. EHG detected a larger number of UCs than TOCO, which is closer to maternal perception. The duration and frequency of UC obtained from EHG and TOCO were not significantly different (p > 0.05). In conclusion, the proposed UC recognition algorithm has high accuracy and simple calculation which could be used for real-time analysis of EHG signals and long-term monitoring of UCs.

M-mode Ultrasound Scan as a Potential Alternative Technique for Monitoring Uterine Contractions in Obese Patients

We investigate motion mode (M-mode) ultrasound scan as a potential non-invasive uterine monitoring technique and compare its contraction characteristics with external tocodynamometry (TOCO). This prospective diagnostic accuracy study included 39 term pregnant woman in active spontaneous labor. M-mode and TOCO were simultaneously performed and uterine contraction characteristics and consistency were compared quantitatively and visually. The results identified a 71.5% ± 35.3% uterine wall thickening during uterine contractions on M-mode. Uterine monitoring with M-mode had a consistency rate of 88.7% ± 6.9% with conventional TOCO method. During 20-min monitoring, the number of detected contractions was significantly higher (p < 0.001) in M-mode (8.2 ± 1.2) than TOCO (7.4 ± 1.5). As for the mean value of the duration of a contraction (seconds), it was significantly shorter (p < 0.001) in M-mode (38.5 ± 3.5) than TOCO (49.2 ± 4.1). For M-mode, the number of detected contractions had a negative but insignificant correlation with the body mass index (BMI) (r = - 0.25 [- 0.52, 0.07], p = 0.127) and the subcutaneous tissue thickness (STT) (r = - 0.21 [- 0.49, 0.11], p = 0.200). As for TOCO, the contractions had a negative and significant correlation with BMI (r = - 0.41 [- 0.64, - 0.11], p = 0.009) and negative and insignificant correlation with STT (r = - 0.26 [- 0.54, 0.06], p = 0.104). The evidence suggests that contraction detection with M-mode is a promising non-invasive technique for uterine monitoring. The preliminary analysis finds that contraction detection is not affected by BMI or STT. With future sensitivity studies, and improvements in image-processing and software technologies, the proposed technique promises to be a viable alternative to existing techniques, especially for obese patients.

Overly optimistic prediction results on imbalanced data: a case study of flaws and benefits when applying over-sampling

Information extracted from electrohysterography recordings could potentially prove to be an interesting additional source of information to estimate the risk on preterm birth. Recently, a large number of studies have reported near-perfect results to distinguish between recordings of patients that will deliver term or preterm using a public resource, called the Term/Preterm Electrohysterogram database. However, we argue that these results are overly optimistic due to a methodological flaw being made. In this work, we focus on one specific type of methodological flaw: applying over-sampling before partitioning the data into mutually exclusive training and testing sets. We show how this causes the results to be biased using two artificial datasets and reproduce results of studies in which this flaw was identified. Moreover, we evaluate the actual impact of over-sampling on predictive performance, when applied prior to data partitioning, using the same methodologies of related studies, to provide a realistic view of these methodologies' generalization capabilities. We make our research reproducible by providing all the code under an open license.

Qualitative assessment of interpretability and observer agreement of three uterine monitoring techniques

OBJECTIVE

The aim of this research was to assess the quality and inter- and intra-observer agreement of tracings obtained by three different techniques for uterine contraction monitoring: the external tocodynamometer (TOCO), the intrauterine pressure catheter (IUPC) and a recently introduced method based on electrohysterography (EHG).

STUDY DESIGN

We included 150 uterine activity registrations from a previous prospective observational study (W3 study), conducted at Máxima Medical Centre in Veldhoven, the Netherlands. Term singleton pregnant women were simultaneously monitored with TOCO, IUPC and EHG during labor. Six clinicians, blinded to the source (TOCO, IUPC, or EHG) and subject, evaluated all tracings that were subsequently presented in random order. They annotated contractions and assigned each tracing a score for interpretability of 2 (good), 1 (moderate) or 0 (poor). To evaluate inter-observer agreement, we calculated kappa values for the qualitative assessment, and intraclass correlation coefficients (ICC) for the number of contractions annotated by clinicians. Four clinicians repeated this procedure to evaluate intra-observer agreement.

RESULTS

IUPC tracings received the highest quality rating, with a mean score of 1.95, followed by a mean score of 1.60 for EHG and 0.80 for TOCO (p < 0.05). Mean weighted kappa values were 0.63 for TOCO and 0.45 for EHG. The average number of contractions that was picked up by clinicians was 59.8 for the intrauterine pressure catheter, 49.8 for EHG and 26.4 for TOCO. The ICC of the intrauterine pressure catheter was significantly higher than the external methods, regarding both inter- and intra-observer agreement (0.98 and 0.99 respectively).

CONCLUSION

IUPC recordings scored best regarding quality, inter- and intra-observer agreement. However, due to safety issues, in many countries this technique is not used anymore. The quality of TOCO was rated as poor and many contractions were missed as compared to the gold standard. From a clinical interpretational point of view, EHG is favorable to TOCO. EHG recordings were assigned higher quality scores, but with less agreement between clinicians. An explanation could be that EHG is a relatively new technique, while IUPC and the TOCO are being used for decades. Building experience with EHG (training) is therefore recommended.

Uterine contractions clustering based on electrohysterography

The uterine electromyogram, also named Electrohysterogram (EHG), is a non-invasive technique that has been used for pregnancy and labour monitoring as well as for research work on uterine physiology. This technique is well established in this field. There is however a vast unexplored potential in the EHG that is currently the subject of interdisciplinary research work involving different scientific fields such as medicine, engineering, physics and mathematics. In this paper, an unsupervised clustering method is applied to a previously obtained set of frequency spectral representations of the respective EHG signal contractions that were previously automatically detected and delineated. An innovative approach using the complete spectrum projection is described, rather than a set of relevant points. The feasibility of the method is established despite the concerns of possible computational burden incurred by the processing of the whole spectrum. Given the unsupervised nature of this classification, a validation procedure was performed whereas the obtained clusters were labelled through the correlation with the common knowledge about the most relevant uterine contraction types, as described in the literature. As a result of this study, a spectral description of the Alvarez contractions was obtained where it was possible to breakdown these important events in two different types according to their spectrum. Spectral estimates of Braxton-Hicks contractions were also obtained and associated to one of the clusters. This led to a full spectral characterization of these uterine events.

Intrauterine versus external tocodynamometry in monitoring labour: a randomised controlled clinical trial

OBJECTIVE

To investigate whether the use of intrauterine tocodynamometry versus external tocodynamometry (IT versus ET) during labour reduces operative deliveries and improves newborn outcome. As IT provides more accurate information on labour contractions, the hypothesis was that it may more appropriately guide oxytocin use than ET.

DESIGN

Randomised controlled trial.

SETTING

Two labour wards, in a university tertiary hospital and a central hospital.

POPULATION

A total of 1504 parturients with singleton pregnancies, gestational age ≥37 weeks and fetus in cephalic position: 269 women with uterine scars, 889 nulliparas and 346 parous women with oxytocin augmentation.

METHODS

Participants underwent IT (n = 736) or ET (n = 768) during the active first stage of labour.

MAIN OUTCOME MEASURES

Primary outcome: rate of operative deliveries.

SECONDARY OUTCOMES

duration of labour, amount of oxytocin given, adverse neonatal outcomes.

RESULTS

Operative delivery rates were 26.9% (IT) and 25.9% (ET) (odds ratio 1.05, 95% CI 0.84-1.32, P = 0.663). The ET to IT conversion rate was 31%. We found no differences in secondary outcomes (IT versus ET). IT reduced oxytocin use during labours with signs of fetal distress, and trial of labour after caesarean section.

CONCLUSIONS

IT did not reduce the rate of operative deliveries, use of oxytocin, or adverse neonatal outcomes, and it did not shorten labour duration.

TWEETABLE ABSTRACT

IT (versus ET) reduced oxytocin use in high-risk labours but did not influence operative delivery rate or adverse neonatal outcomes.

Robust Characterization of the Uterine Myoelectrical Activity in Different Obstetric Scenarios

Electrohysterography (EHG) has been shown to provide relevant information on uterine activity and could be used for predicting preterm labor and identifying other maternal fetal risks. The extraction of high-quality robust features is a key factor in achieving satisfactory prediction systems from EHG. Temporal, spectral, and non-linear EHG parameters have been computed to characterize EHG signals, sometimes obtaining controversial results, especially for non-linear parameters. The goal of this work was to assess the performance of EHG parameters in identifying those robust enough for uterine electrophysiological characterization. EHG signals were picked up in different obstetric scenarios: antepartum, including women who delivered on term, labor, and post-partum. The results revealed that the 10th and 90th percentiles, for parameters with falling and rising trends as labor approaches, respectively, differentiate between these obstetric scenarios better than median analysis window values. Root-mean-square amplitude, spectral decile 3, and spectral moment ratio showed consistent tendencies for the different obstetric scenarios as well as non-linear parameters: Lempel–Ziv, sample entropy, spectral entropy, and SD1/SD2 when computed in the fast wave high bandwidth. These findings would make it possible to extract high quality and robust EHG features to improve computer-aided assessment tools for pregnancy, labor, and postpartum progress and identify maternal fetal risks.

Uterine expression of smooth muscle alpha- and gamma-actin and smooth muscle myosin in bitches diagnosed with uterine inertia and obstructive dystocia

Primary uterine inertia (PUI) is the most common type of dystocia in dogs. We hypothesized that PUI develops because of lower than normal expression of the basic contractile elements in the uterus, i.e., smooth muscle (SM) α- and γ-actin and SM-myosin, and that the expression of these proteins is influenced by the number of fetuses present in utero. Full-thickness inter-placental uterine biopsies were collected during Cesarean sections from dogs with PUI (n = 11), and from bitches with obstructive dystocia (OD) still presenting strong labor contractions (designated as the control group, n = 7). Relative gene expression was determined by semi-quantitative real-time (TaqMan) PCR, and protein localization by immunohistochemistry. Gene expression between PUI and OD bitches, and between PUI bitches carrying small, large, or average number of fetuses according to their breed, were compared. Uterine SM-γ-actin and SM-myosin mRNA levels were significantly higher in PUI than in OD dogs, while SM-α-actin did not differ. PUI bitches carrying large litters had lower uterine SM-γ-actin gene expression than those with small litters (P = 0.008). Immunostaining for SM-actin isoforms and SM-myosin was present in the myometrium, and localization pattern and staining intensity appeared similar in the PUI and OD groups. All proteins stained in blood vessels, and SM-γ-actin was also present in endometrial luminal and glandular epithelium. In conclusion, higher uterine SM-γ-actin and SM-myosin gene expression in PUI bitches, compared with OD dogs, might be an indication of abnormal progression with labor. Whether this is the cause of PUI due to an intrinsic error of the myometrium not becoming committed to labor, or the consequence of inadequate endocrine or mechanical stimuli, is not clear. Litter size was previously shown to be one of the risk factors for the development of uterine inertia in dogs, and our findings suggest possible differing uterine pathophysiology of PUI with respect to litter size.

Characterization of EHG Contractions at Pregnancy and Term Labor by Multiscale Entropy Analysis

Monitoring uterine activity by electrohysterogram (EHG), associated with contractions both in pregnancy and labor, may contribute to the knowledge for evaluating possible risks to the binomial mother-fetus. In this context, the aim of the present study was to explore the complexity of EHG generated by women during the third trimester of pregnancy (group P) and at term labor (group L). The EHG was obtained by band-pass filtering in the range from 0.1 to 3 Hz the monopolar raw signal of the electrode number 1, of a 4-by-4 sensor array, which was located near to the tocodynamometer transducer. Multiscale entropy (MSE) analysis measures the entropy over multiple time scales to provide the complexity of the EHG time series. The results pointed out that such nonlinear technique has the potential to discriminate contractions from both groups using the area under the MSE curve (AUC) as index. The highest complexity was obtained for group P (N= 8) as AUC was 13.9233 ± 0.2015 while the lowest complexity was for group L, with N=8 and AUC of 5.1675 ± 0.0783 (p<; 0.0001). Consequently, the complexity of EHG by MSE could provide an index to discriminate between the electrical uterine activity generated during pregnancy or at labor.

Spatial-dependent regularization to solve the inverse problem in electromyometrial imaging

Recently, electromyometrial imaging (EMMI) was developed to non-invasively image uterine contractions in three dimensions. EMMI collects body surface electromyography (EMG) measurements and uses patient-specific body-uterus geometry generated from magnetic resonance images to reconstruct uterine electrical activity. Currently, EMMI uses the zero-order Tikhonov method with mean composite residual and smoothing operator (CRESO) to stabilize the underlying ill-posed inverse computation. However, this method is empirical and implements a global regularization parameter over all uterine sites, which is sub-optimal for EMMI given the severe eccentricity of body-uterus geometry. To address this limitation, we developed a spatial-dependent (SP) regularization method that considers both body-uterus eccentricity and EMG noise. We used electrical signals simulated with spherical and realistic geometry models to compare the reconstruction accuracy of the SP method to those of the CRESO and the L-Curve methods. The SP method reconstructed electrograms and potential maps more accurately than the other methods, especially in cases of high eccentricity and noise contamination. Thus, the SP method should facilitate clinical use of EMMI and can be used to improve the accuracy of other electrical imaging modalities, such as Electrocardiographic Imaging. Graphical abstract The spatial-dependent regularization (SP) technique was designed to improve the accuracy of Electromyometrial Imaging (EMMI). The top panel shows the eccentricity of body-uterus geometry and four representative body surface electrograms. The bottom panel shows boxplots of correlation coefficients and relative errors for the electrograms reconstructed with SP and two conventional methods, the L-Curve and mean CRESO methods.

A Comparative Study of Vaginal Labor and Caesarean Section Postpartum Uterine Myoelectrical Activity

Postpartum hemorrhage (PPH) is one of the major causes of maternal mortality and morbidity worldwide, with uterine atony being the most common origin. Currently there are no obstetrical techniques available for monitoring postpartum uterine dynamics, as tocodynamometry is not able to detect weak uterine contractions. In this study, we explored the feasibility of monitoring postpartum uterine activity by non-invasive electrohysterography (EHG), which has been proven to outperform tocodynamometry in detecting uterine contractions during pregnancy. A comparison was made of the temporal, spectral, and non-linear parameters of postpartum EHG characteristics of vaginal deliveries and elective cesareans. In the vaginal delivery group, EHG obtained a significantly higher amplitude and lower kurtosis of the Hilbert envelope, and spectral content was shifted toward higher frequencies than in the cesarean group. In the non-linear parameters, higher values were found for the fractal dimension and lower values for Lempel-Ziv, sample entropy and spectral entropy in vaginal deliveries suggesting that the postpartum EHG signal is extremely non-linear but more regular and predictable than in a cesarean. The results obtained indicate that postpartum EHG recording could be a helpful tool for earlier detection of uterine atony and contribute to better management of prophylactic uterotonic treatment for PPH prevention.

Intrapartum non-invasive electrophysiological monitoring: A prospective observational study

INTRODUCTION

Doppler ultrasound cardiotocography is a non-invasive alternative that, despite its poor specificity, is often first choice for intrapartum monitoring. Doppler ultrasound suffers from signal loss due to fetal movements and is negatively correlated with maternal body mass index (BMI). Reported accuracy of fetal heart rate monitoring by Doppler ultrasound varies between 10.6 and 14.3 bpm and reliability between 62.4% and 73%. The fetal scalp electrode (FSE) is considered the reference standard for fetal monitoring but can only be applied after membranes have ruptured with sufficient cervical dilatation and is sometimes contra-indicated. A non-invasive alternative that overcomes the shortcomings of Doppler ultrasound, providing reliable information on fetal heart rate, could be the answer. Non-invasive fetal electrocardiography (NI-fECG) uses a wireless electrode patch on the maternal abdomen to obtain both fetal and maternal heart rate signals as well as an electrohysterogram. We aimed to validate a wireless NI-fECG device for intrapartum monitoring in term singleton pregnancies, by comparison with the FSE.

MATERIAL AND METHODS

We performed a multicenter cross-sectional observational study at labor wards of 6 hospitals located in the Netherlands, Belgium, and Spain. Laboring women with a healthy singleton fetus in cephalic presentation and gestational age between 36 and 42 weeks were included. Participants received an abdominal electrode patch and FSE after written informed consent. Accuracy, reliability, and success rate of fetal heart rate readings were determined, using FSE as reference standard. Analysis was performed for the total population and measurement period as well as separated by labor stage and BMI class (≤30 and >30 kg/m² ).

RESULTS

We included a total of 125 women. Simultaneous registrations with NI-fECG and FSE were available in 103 women. Overall accuracy is -1.46 bpm and overall reliability 86.84%. Overall success rate of the NI-fECG is around 90% for the total population as well as for both BMI subgroups. Success rate dropped to 63% during second stage of labor, similar results are found when looking at the separate BMI groups.

CONCLUSIONS

Performance measures of the NI-fECG device are good in the overall group and the separate BMI groups. Compared with Doppler ultrasound performance measures from the literature, NI-fECG is a more accurate alternative. Especially, when women have a higher BMI, NI-fECG performs well, resembling FSE performance measures.

Electrohysterogram for ANN-Based Prediction of Imminent Labor in Women with Threatened Preterm Labor Undergoing Tocolytic Therapy

Threatened preterm labor (TPL) is the most common cause of hospitalization in the second half of pregnancy and entails high costs for health systems. Currently, no reliable labor proximity prediction techniques are available for clinical use. Regular checks by uterine electrohysterogram (EHG) for predicting preterm labor have been widely studied. The aim of the present study was to assess the feasibility of predicting labor with a 7- and 14-day time horizon in TPL women, who may be under tocolytic treatment, using EHG and/or obstetric data. Based on 140 EHG recordings, artificial neural networks were used to develop prediction models. Non-linear EHG parameters were found to be more reliable than linear for differentiating labor in under and over 7/14 days. Using EHG and obstetric data, the <7- and <14-day labor prediction models achieved an AUC in the test group of 87.1 ± 4.3% and 76.2 ± 5.8%, respectively. These results suggest that EHG can be reliable for predicting imminent labor in TPL women, regardless of the tocolytic therapy stage. This paves the way for the development of diagnostic tools to help obstetricians make better decisions on treatments, hospital stays and admitting TPL women, and can therefore reduce costs and improve maternal and fetal wellbeing.

Critical analysis of electrohysterographic methods for continuous monitoring of intrauterine pressure

Monitoring the progression of uterine activity provides important prognostic information during pregnancy and delivery. Currently, uterine activity monitoring relies on direct or indirect mechanical measurements of intrauterine pressure (IUP), which are unsuitable for continuous long-term observation. The electrohysterogram (EHG) provides a non-invasive alternative to the existing methods and is suitable for long-term ambulatory use. Several published state-of-the-art methods for EHG-based IUP estimation are here discussed, analyzed, optimized, and compared. By means of parameter space exploration, key parameters of the methods are evaluated for their relevance and optimal values. We have optimized all methods towards higher IUP estimation accuracy and lower computational complexity. Their accuracy was compared with the gold standard accuracy of internally measured IUP. Their computational complexity was compared based on the required number of multiplications per second (MPS). Significant reductions in computational complexity have been obtained for all published algorithms, while improving IUP estimation accuracy. A correlation coefficient of 0.72 can be obtained using fewer than 120 MPS. We conclude that long-term ambulatory monitoring of uterine activity is possible using EHG-based methods. Furthermore, the choice of a base method for IUP estimation is less important than the correct selection of electrode positions, filter parameters, and postprocessing methods. The presented review of state-of-the-art methods and applied optimizations show that long-term ambulatory IUP monitoring is feasible using EHG measurements.

Contractions: Traditional concepts and their role in modern obstetrics

Contractions are produced through a complex interplay of hormonal, mechanical, and electrical factors. In labor, contractions are measured using the Montevideo unit. Clinical considerations in labor wherein contraction assessment becomes paramount include the care of women whose labor is complicated by abnormal progress or tachysystole. In an era of obstetrics in which the high cesarean rate is a major issue of concern, there remain many questions as to how to best incorporate contraction monitoring into practice in order to optimize care. Technological advancement has led to the development on new modalities that can be used to study contraction physiology, and there may be an opportunity in the future to apply these methods for use in the clinical setting. This article also makes a case for the need to reevaluate the current measures of uterine contractile activity and the definition of contraction adequacy using updated definitions of normal labor progress.

Noninvasive high-resolution electromyometrial imaging of uterine contractions in a translational sheep model

In current clinical practice, uterine contractions are monitored via a tocodynamometer or an intrauterine pressure catheter, both of which provide crude information about contractions. Although electrohysterography/electromyography can measure uterine electrical activity, this method lacks spatial specificity and thus cannot accurately measure the exact location of electrical initiation and location-specific propagation patterns of uterine contractions. To comprehensively evaluate three-dimensional uterine electrical activation patterns, we describe here the development of electromyometrial imaging (EMMI) to display the three-dimensional uterine contractions at high spatial and temporal resolution. EMMI combines detailed body surface electrical recording with body-uterus geometry derived from magnetic resonance images. We used a sheep model to show that EMMI can reconstruct uterine electrical activation patterns from electrodes placed on the abdomen. These patterns closely match those measured with electrodes placed directly on the uterine surface. In addition, modeling experiments showed that EMMI reconstructions are minimally affected by noise and geometrical deformation. Last, we show that EMMI can be used to noninvasively measure uterine contractions in sheep in the same setup as would be used in humans. Our results indicate that EMMI can noninvasively, safely, accurately, robustly, and feasibly image three-dimensional uterine electrical activation during contractions in sheep and suggest that similar results might be obtained in clinical setting.

Non-invasive Fetal Electrocardiography for Intrapartum Cardiotocography

Fetal monitoring is important to diagnose complications that can occur during pregnancy. If detected timely, these complications might be resolved before they lead to irreversible damage. Current fetal monitoring mainly relies on cardiotocography, the simultaneous registration of fetal heart rate and uterine activity. Unfortunately, the technology to obtain the cardiotocogram has limitations. In current clinical practice the fetal heart rate is obtained via either an invasive scalp electrode, that poses risks and can only be applied during labor and after rupture of the fetal membranes, or via non-invasive Doppler ultrasound technology that is inaccurate and suffers from loss of signal, in particular in women with high body mass, during motion, or in preterm pregnancies. In this study, transabdominal electrophysiological measurements are exploited to provide fetal heart rate non-invasively and in a more reliable manner than Doppler ultrasound. The performance of the fetal heart rate detection is determined by comparing the fetal heart rate to that obtained with an invasive scalp electrode during intrapartum monitoring. The performance is gauged by comparing it to performances mentioned in literature on Doppler ultrasound and on two commercially-available devices that are also based on transabdominal fetal electrocardiography.