Noninvasive uterine electromyography for prediction of preterm delivery

Mid-Pregnancy Ultrasonographic Cervical Length Measurement (A Predictor of Mode and Timing of Delivery): An Observational Study

Objective: Even though cervical length is considered as predictor of timing and mode of delivery, it is not used as a screening tool in low risk asymptomatic population. This study was carried out with the intention to know the timing and mode of delivery in asymptomatic low risk women using second trimester ultrasonographic cervical length measurement and predict the risk of pretermlabor, prolonged pregnancy and need for caesarean section. 1) To determine the association between cervical length at mid-pregnancy and timing of delivery. 2) To determine the usefulness of mid-pregnancy ultrasonographic cervical length measurement in predicting mode of delivery. Materials and methods: Transvaginal sonography was performed to measure the cervical length between 20-24 weeks of gestation. These patients were followed till delivery to assess the gestational age at delivery and mode of delivery. Results: Totally 237 patients were recruited of which 173 satisfied the inclusion criteria. Out of 15 patients with cervical length less than 3cm, 14(93.33%) had preterm delivery. Postdated pregnancy was observed in 45(90%) out of 50 patients with cervical length more than 4cm. In the group with cervical length less than 3cm, 12 (80%) delivered vaginally. Among cervical length more than 4cm group 24 (48%) required cesarean section. Conclusion: Cervical length of less than 3cm measured between 20-24 weeks of gestation is associated with preterm births and favours vaginal birth whereas, cervical length of more than 4cm is associated with postdated pregnancy and increased incidence of cesarean section.

Electrohysterography in the diagnosis of preterm birth: a review

Preterm birth (PTB) is one of the most common and serious complications in pregnancy. About 15 million preterm neonates are born every year, with ratios of 10-15% of total births. In industrialized countries, preterm delivery is responsible for 70% of mortality and 75% of morbidity in the neonatal period. Diagnostic means for its timely risk assessment are lacking and the underlying physiological mechanisms are unclear. Surface recording of the uterine myoelectrical activity (electrohysterogram, EHG) has emerged as a better uterine dynamics monitoring technique than traditional surface pressure recordings and provides information on the condition of uterine muscle in different obstetrical scenarios with emphasis on predicting preterm deliveries.

OBJECTIVE

A comprehensive review of the literature was performed on studies related to the use of the electrohysterogram in the PTB context.

APPROACH

This review presents and discusses the results according to the different types of parameter (temporal and spectral, non-linear and bivariate) used for EHG characterization.

MAIN RESULTS

Electrohysterogram analysis reveals that the uterine electrophysiological changes that precede spontaneous preterm labor are associated with contractions of more intensity, higher frequency content, faster and more organized propagated activity and stronger coupling of different uterine areas. Temporal, spectral, non-linear and bivariate EHG analyses therefore provide useful and complementary information. Classificatory techniques of different types and varying complexity have been developed to diagnose PTB. The information derived from these different types of EHG parameters, either individually or in combination, is able to provide more accurate predictions of PTB than current clinical methods. However, in order to extend EHG to clinical applications, the recording set-up should be simplified, be less intrusive and more robust-and signal analysis should be automated without requiring much supervision and yield physiologically interpretable results.

SIGNIFICANCE

This review provides a general background to PTB and describes how EHG can be used to better understand its underlying physiological mechanisms and improve its prediction. The findings will help future research workers to decide the most appropriate EHG features to be used in their analyses and facilitate future clinical EHG applications in order to improve PTB prediction.

Identification of preterm birth based on RQA analysis of electrohysterograms

BACKGROUND AND OBJECTIVE

Common methods for data analysis are mainly based on linear concepts, but in recent years nonlinear dynamics methods have been introduced. It is a well-known fact that In typical biological systems lack of stationarity and rather sudden changes of state are the properties distinguishing them from each other. There is an urgent need to better understand the mechanical activity of the myometrium (its contractility) to find a solution for preterm delivery problem, the largest cause of neonatal deaths and morbidity. The electrohysterographic signal (EHG) is a good non-linear, bioelectrical indicator for the detection and identification of term and preterm birth.

METHODS

The material of the study consists of EHG signals, obtained from 20 patients between the 24th and the 28th week of pregnancy with threatened preterm labor. The women were divided into two groups: those delivering after more than 7 days - group A (n = 10) and women delivering within 7 days - group B (n = 10). In this paper, an analysis of bioelectrical signals was performed by recurrence quantification analysis (RQA) and principal component analysis (PCA) to distinguish particular patterns for term and preterm birth. To date, these methods have not been used for the evaluation of bioelectrical activity in the uterus. To train novel classifiers for the EHG signals Support Vectors Machine classifications (multiclass SVM) was used. Statistical analysis was performed by means of non-parametric Mann-Whitney test.

RESULTS

From among eleven parameters obtained from recurrence quantification analysis, five most appropriate were chosen: Recurrence Rate, Determinism, Laminarity, Entropy and Recurrence Period Density Entropy. Significant increase (p < .001) of Recurrence Rate was found in patients from group B, while increase of parameters, besides Laminarity, was found in patients from group A. The accuracy of classification obtained as a result of the analysis increased to 83,32%.

CONCLUSION

We showed that the respectively selected recurrence quantificators obtained for that time series could be used to classify all those signals to the appropriate group. The proposed analysis could help in detecting preterm labor based on the EHG signal dynamics.

ESTIMATION OF INTRAUTERINE PRESSURE FROM ELECTROHYSTEROGRAPHY USING HILBERT PHASE SLIPS AND STATISTICS METHOD

Prognostic information during pregnancy can be obtained by monitoring maternal uterine activity. Tocodynamometry (TOCO) is widely used to assess the uterine activity today but it has been found that it has very low sensitivity. Another method to assess the uterine activity is intrauterine pressure catheter (IUPC) which is accurate but highly invasive. Electrohysterogram (EHG) measured from abdominal surface is a noninvasive method to detect uterine contractions. To reduce motion artifacts of intrauterine pressure (IUP) estimated from EHG signal and further improve the accuracy of contractions detected by IUP estimation, we propose a method to divide the EHG signal into segments by using Hilbert phase slips. Standard deviation (STD) was used to estimate IUP from each EHG signal segment and median filter was used to remove the motion artifacts. The method we proposed was compared with other four methods from literatures. The proposed method results in a higher contractions detection accuracy of EHG-based IUP estimation and a higher correlation coefficient with the IUPC signals compared to other methods which demonstrated the capabilities of the proposed method in reducing motion artifacts of IUP estimation based on abdominal EHG.

Dedicated Entropy Measures for Early Assessment of Pregnancy Progression From Single-Channel Electrohysterography

OBJECTIVE

Preterm birth is a large-scale clinical problem involving over 10% of infants. Diagnostic means for timely risk assessment are lacking and the underlying physiological mechanisms unclear. To improve the evaluation of pregnancy before term, we introduce dedicated entropy measures derived from a single-channel electrohysterogram (EHG).

METHODS

The estimation of approximate entropy (ApEn) and sample entropy (SampEn) is adjusted to monitor variations in the regularity of single-channel EHG recordings, reflecting myoelectrical changes due to pregnancy progression. In particular, modifications in the tolerance metrics are introduced for improving robustness to EHG amplitude fluctuations. An extensive database of 58 EHG recordings with 4 monopolar channels in women presenting with preterm contractions was manually annotated and used for validation. The methods were tested for their ability to recognize the onset of labor and the risk of preterm birth. Comparison with the best single-channel methods according to the literature was performed.

RESULTS

The reference methods were outperformed. SampEn and ApEn produced the best prediction of delivery, although only one channel showed a significant difference () between labor and nonlabor. The modified ApEn produced the best prediction of preterm delivery, showing statistical significance () in three channels. These results were also confirmed by the area under the receiver operating characteristic curve and fivefold cross validation.

CONCLUSION

The use of dedicated entropy estimators improves the diagnostic value of EHG analysis earlier in pregnancy.

SIGNIFICANCE

Our results suggest that changes in the EHG might manifest early in pregnancy, providing relevant prognostic opportunities for pregnancy monitoring by a practical single-channel solution.

Prediction of labor onset type: Spontaneous vs induced; role of electrohysterography?

BACKGROUND AND OBJECTIVE

Induction of labor (IOL) is a medical procedure used to initiate uterine contractions to achieve delivery. IOL entails medical risks and has a significant impact on both the mother's and newborn's well-being. The assistance provided by an automatic system to help distinguish patients that will achieve labor spontaneously from those that will need late-term IOL would help clinicians and mothers to take an informed decision about prolonging pregnancy. With this aim, we developed and evaluated predictive models using not only traditional obstetrical data but also electrophysiological parameters derived from the electrohysterogram (EHG).

METHODS

EHG recordings were made on singleton term pregnancies. A set of 10 temporal and spectral parameters was calculated to characterize EHG bursts and a further set of 6 common obstetrical parameters was also considered in the predictive models design. Different models were implemented based on single layer Support Vector Machines (SVM) and with aggregation of majority voting of SVM (double layer), to distinguish between the two groups: term spontaneous labor (≤41 weeks of gestation) and IOL late-term labor. The areas under the curve (AUC) of the models were compared.

RESULTS

The obstetrical and EHG parameters of the two groups did not show statistically significant differences. The best results of non-contextualized single input parameter SVM models were achieved by the Bishop Score (AUC= 0.65) and GA at recording time (AUC= 0.68) obstetrical parameters. The EHG parameter median frequency, when contextualized with the two obstetrical parameters improved these results, reaching AUC= 0.76. Multiple input SVM obtained AUC= 0.70 for all EHG parameters. Aggregation of majority voting of SVM models using contextualized EHG parameters achieved the best result AUC= 0.93.

CONCLUSIONS

Measuring the electrophysiological uterine condition by means of electrohysterographic recordings yielded a promising clinical decision support system for distinguishing patients that will spontaneously achieve active labor before the end of full term from those who will require late term IOL. The importance of considering these EHG measurements in the patient's individual context was also shown by combining EHG parameters with obstetrical parameters. Clinicians considering elective labor induction would benefit from this technique.

Biomathematical pattern of EMG signal propagation in smooth muscle of the non-pregnant porcine uterus

Uterine contractions are generated by myometrial smooth muscle cells (SMCs) that comprise most of the myometrial layer of the uterine wall. Aberrant uterine motility (i.e., hypo- or hyper-contractility or asynchronous contractions) has been implicated in the pathogenesis of infertility due to the failure of implantation, endometriosis and abnormal estrous cycles. The mechanism whereby the non-pregnant uterus initiates spontaneous contractions remains poorly understood. The aim of the present study was to employ linear synchronization measures for analyzing the pattern of EMG signal propagation (direction and speed) in smooth muscles of the non-pregnant porcine uterus in vivo using telemetry recording system. It has been revealed that the EMG signal conduction in the uterine wall of the non-pregnant sow does not occur at random but it rather exhibits specific directions and speed. All detectable EMG signals moved along the uterine horn in both cervico-tubal and tubo-cervical directions. The signal migration speed could be divided into the three main types or categories: i. slow basic migration rhythm (SBMR); ii. rapid basic migration rhythm (RBMR); and iii. rapid accessory migration rhythm (RAMR). In conclusion, the EMG signal propagation in smooth muscles of the porcine uterus in vivo can be assessed using a linear synchronization model. Physiological pattern of the uterine contractile activity determined in this study provides a basis for future investigations of normal and pathologicall myogenic function of the uterus.

A node-wise analysis of the uterine muscle networks for pregnancy monitoring

The recent past years have seen a noticeable increase of interest in the correlation analysis of electrohysterographic (EHG) signals in the perspective of improving the pregnancy monitoring. Here we propose a new approach based on the functional connectivity between multichannel (4×4 matrix) EHG signals recorded from the women's abdomen. The proposed pipeline includes i) the computation of the statistical couplings between the multichannel EHG signals, ii) the characterization of the connectivity matrices, computed by using the imaginary part of the coherence, based on the graph-theory analysis and iii) the use of these measures for pregnancy monitoring. The method was evaluated on a dataset of EHGs, in order to track the correlation between EHGs collected by each electrode of the matrix (called `node-wise' analysis) and follow their evolution along weeks before labor. Results showed that the strength of each node significantly increases from pregnancy to labor. Electrodes located on the median vertical axis of the uterus seemed to be the more discriminant. We speculate that the network-based analysis can be a very promising tool to improve pregnancy monitoring.

Uterine and Abdominal Muscle Electromyographic Activities in Control and PCEA-Treated Nulliparous Women During the Second Stage of Labor

OBJECTIVE

Patient-controlled epidural analgesia (PCEA), used to relieve pain during delivery, delays labor but the mechanism is unknown. The aim was to investigate the effects of PCEA on uterine and abdominal muscles electromyographic (EMG) activity during the second stage of labor.

METHODS

This study included 45 nulliparous pregnant women without PCEA, 42 women with standard PCEA treatment given during the first stage of labor and stopped near the end of the first stage, and 22 women with standard PCEA treatment with continued use throughout the first and second stages of labor. The EMG signals were recorded from the abdominal surface using PowerLab hardware and LabChart software (ADInstruments, New South Wales, Australia) and filtered to separate uterine and abdominal EMG. Various EMG burst parameters were obtained.

RESULTS

There are no differences ( P > .05) in the age, body mass index, fetal weight, and Apgar scores between the patients from the various groups. PCEA (both stopped and continued) inhibits ( P < .05) duration, number of bursts, and root mean square of uterine EMG. PCEA also produces statistically significant ( P < .001) reductions in abdominal EMG. The decrease in EMG activity is accompanied by a significant ( P < .001) prolongation of the second stage duration (PCEA continued = 95.08 ± 8.60 minutes, PCEA stopped = 79.39 ± 6.25 minutes, no PCEA = 61.00 ± 7.23 minutes).

CONCLUSION

PCEA suppresses uterine and abdominal muscle EMG during the second stage of labor but inhibition depends upon the treatment schedule. PCEA prolongs the duration of labor by inhibition of uterine and abdominal muscle and neural activity.

Effect of obesity on preterm delivery prediction by transabdominal recording of uterine electromyography

OBJECTIVE

It has been shown that noninvasive uterine electromyography (EMG) can identify true preterm labor more accurately than methods available to clinicians today. The objective of this study was to evaluate the effect of body mass index (BMI) on the accuracy of uterine EMG in predicting preterm delivery.

MATERIALS AND METHODS

Predictive values of uterine EMG for preterm delivery were compared in obese versus overweight/normal BMI patients. Hanley-McNeil test was used to compare receiver operator characteristics curves in these groups. Previously reported EMG cutoffs were used to determine groups with false positive/false negative and true positive/true negative EMG results. BMI in these groups was compared with Student t test (p < 0.05 significant).

RESULTS

A total of 88 patients were included: 20 obese, 64 overweight, and four with normal BMI. EMG predicted preterm delivery within 7 days with area under the curve = 0.95 in the normal/overweight group, and with area under the curve = 1.00 in the obese group (p = 0.08). Six patients in true preterm labor (delivering within 7 days from EMG measurement) had low EMG values (false negative group). There were no false positive results. No significant differences in patient's BMI were noted between false negative group patients and preterm labor patients with high EMG values (true positive group) and nonlabor patients with low EMG values (true negative group; p = 0.32).

CONCLUSION

Accuracy of noninvasive uterine EMG monitoring and its predictive value for preterm delivery are not affected by obesity.

Simultaneous Recording and Analysis of Uterine and Abdominal Muscle Electromyographic Activity in Nulliparous Women During Labor

OBJECTIVE

To record and characterize electromyography (EMG) from the uterus and abdominal muscles during the nonlabor to first and second stages of labor and to define relationships to contractions.

METHODS

Nulliparous patients without any treatments were used (n = 12 nonlabor stage, 48 during first stage and 33 during second stage). Electromyography of both uterine and abdominal muscles was simultaneously recorded from electrodes placed on patients' abdominal surface using filters to separate uterine and abdominal EMG. Contractions of muscles were also recorded using tocodynamometry. Electromyography was characterized by analysis of various parameters.

RESULTS

During the first stage of labor, when abdominal EMG is absent, uterine EMG bursts temporally correspond to contractions. In the second stage, uterine EMG bursts usually occur at same frequency as groups of abdominal bursts and precede abdominal bursts, whereas abdominal EMG bursts correspond to contractions and are accompanied by feelings of "urge to push." Uterine EMG increases progressively from nonlabor to second stage of labor.

CONCLUSIONS

(1) Uterine EMG activity can be separated from abdominal EMG events by filtering. (2) Uterine EMG gradually evolves from the antepartum stage to the first and second stages of labor. (3) Uterine and abdominal EMG reflect electrical activity of the muscles during labor and are valuable to assess uterine and abdominal muscle events that control labor. (4) During the first stage of labor uterine, EMG is responsible for contractions, and during the second stage, both uterine and abdominal muscle participate in labor.

Mechanotransduction mechanisms for coordinating uterine contractions in human labor

This review presents evolving concepts of how the human uterus contracts in pregnancy, with emphasis on the mechanisms of long-distance signaling. Action potential propagation has historically been assumed to be the sole mechanism for signaling and tissue recruitment over both short and long distances. However, data in animals and humans indicate that a single action potential does not travel distances greater than a few centimeters. To address this enigma, a long-distance signaling mechanism based on hydraulic signaling and mechanotransduction is developed. By combining this mechanism for long-distance signaling with the action potential propagation mechanism for signaling over short distances, a comprehensive dual mechanism model (or 'dual model') of uterine function is formulated. Mechanotransduction is an accepted phenomenon of myometrium, but the dual model identifies mechanotransduction as relevant to normal labor. For hydraulic signaling, a local contraction slightly increases intrauterine pressure, which globally increases wall tension. Increased wall tension then mechanically induces additional local contractions that further raise pressure. This leads to robust, positive feedback recruitment that explains the emergence of consistently strong contractions of human labor. Three key components of the dual model - rapid long-distance signaling, mechanical triggering, and electrical activity - converge with the concept of mechanically sensitive electrogenic pacemakers distributed throughout the wall. The dual model retains excitation-contraction coupling and action potential propagation for signaling over short distances (<10cm) and hence is an extension of the action potential model rather than a replacement.

Analysis of uterine activity in nonpregnant women by electrohysterography: A feasibility study

With an overall effectiveness below 30%, in vitro fertilization (IVF) is in urgent need for improvements, especially in view of the increasing trend in postponing childbirth in developed societies. Abnormal contraction of the uterus may underlie impaired fertility and unsuccessful IVF. However, currently, there is no method for quantitative assessment of uterine activity and guidance of dedicated intervention. Analysis of the electrohysterogram (EHG) has been extensively used in pregnancy for quantifying uterine contractions. In this paper, we evaluate, for the first time, the use of EHG analysis for characterizing contractions in women in two different phases of the menstrual cycle, when the uterus is expected to be active and quiescent. In this preliminary study, by estimating the time evolution of the EHG signal energy, we derive the contraction frequency, fC, as a possible marker for quantifying the activity of the uterus and discriminate between active and quiescent status. Ultrasound (US) image sequences are simultaneously recorded and visually analyzed for a qualitative validation of the results. The high correlation (0.91) between fC obtained by EHG and US analysis and the measured different values of fC in the two phases motivate further research to confirm the value of EHG analysis for contraction quantification in nonpregnant women.

Characterizing the Propagation of Uterine Electrophysiological Signals Recorded with a Multi-Sensor Abdominal Array in Term Pregnancies

The objective of this study was to quantify the number of segments that have contractile activity and determine the propagation speed from uterine electrophysiological signals recorded over the abdomen. The uterine magnetomyographic (MMG) signals were recorded with a 151 channel SARA (SQUID Array for Reproductive Assessment) system from 36 pregnant women between 37 and 40 weeks of gestational age. The MMG signals were scored and segments were classified based on presence of uterine contractile burst activity. The sensor space was then split into four quadrants and in each quadrant signal strength at each sample was calculated using center-of-gravity (COG). To this end, the cross-correlation analysis of the COG was performed to calculate the delay between pairwise combinations of quadrants. The relationship in propagation across the quadrants was quantified and propagation speeds were calculated from the delays. MMG recordings were successfully processed from 25 subjects and the average values of propagation speeds ranged from 1.3-9.5 cm/s, which was within the physiological range. The propagation was observed between both vertical and horizontal quadrants confirming multidirectional propagation. After the multiple pairwise test (99% CI), significant differences in speeds can be observed between certain vertical or horizontal combinations and the crossed pair combinations. The number of segments containing contractile activity in any given quadrant pair with a detectable delay was significantly higher in the lower abdominal pairwise combination as compared to all others. The quadrant-based approach using MMG signals provided us with high spatial-temporal information of the uterine contractile activity and will help us in the future to optimize abdominal electromyographic (EMG) recordings that are practical in a clinical setting.

The association between myometrial electrical activity and time to delivery in threatened preterm labor

OBJECTIVE

To assess the association between myometrial electrical activity and time-to-delivery in preterm labor using uterine electromyography.

METHODS

Myometrial electrical activity was measured via the electrical uterine monitor (EUM) device. Data was prospectively collected among women admitted due to suspected preterm labor, prior to 34 weeks of gestation. EUM-Index was defined as the mean electrical activity of the uterine muscle over a period of 10 minutes measured in units of microjoule (μJ, microwatt second). The association between the EUM-Index at admission to time-to-delivery and delivery prior to 34 weeks of gestation was calculated.

RESULTS

Overall, 45 women were included in the study. EUM-Index combined with cervical dilatation, demonstrated significant correlation to time-to-delivery (R(2 )= 0.49, p = 0.005), which was strengthened for women presenting prior to 28 weeks of gestation. EUM-Index above the median (>3.05 MJ) was significantly associated with a shorter latency period for delivery (36.0 ± 19.4 vs. 50.2 ± 25.9 days, p = 0.04). For delivery prior to 34 weeks, the EUM-Index showed an AUC = 0.65 (95% CI 0.48-0.82), and a cutoff of 2.5 MJ provided 91.7% sensitivity and 93.3% negative predictive value.

CONCLUSION

EUM-Index at time of admission due to suspected preterm labor is inversely correlated with time-to-delivery and may effectively rule out preterm delivery prior to 34 weeks.

Electrohysterographic detection of uterine contractions in term pregnancy

Uterine-contraction detection is a fundamental component of pregnancy monitoring. Electrohysterography (EHG) provides a non-invasive and accurate alternative to intrauterine pressure (IUP) measurements, and several techniques provide an estimated IUP (eIUP) based on the EHG alone. Commonly, EHG contraction detection is based on amplitude thresholding of the eIUP. We aim at improving the reliability of contraction detection, such that automatic contraction detection can be realized. An algorithm for template-matching of the eIUP signal is proposed. This method is based on Bayesian evidence using a Gaussian likelihood function to classify uterine activity. Gaussian templates are matched to the input signal, with weights obtained empirically from manually-annotated contraction events in a training data-set. The results show an improvement in contraction detection accuracy compared to threshold-based methods. The template-matching method is adaptable to relevant features in the input training data, and is thus less sensitive to differences in eIUP derivation or measurement variability. The method allows for improved automatic uterine contraction detection in labor EHG data, while being extensible to e.g. preterm contraction detection.

Improved Prediction of Preterm Delivery Using Empirical Mode Decomposition Analysis of Uterine Electromyography Signals

Preterm delivery increases the risk of infant mortality and morbidity, and therefore developing reliable methods for predicting its likelihood are of great importance. Previous work using uterine electromyography (EMG) recordings has shown that they may provide a promising and objective way for predicting risk of preterm delivery. However, to date attempts at utilizing computational approaches to achieve sufficient predictive confidence, in terms of area under the curve (AUC) values, have not achieved the high discrimination accuracy that a clinical application requires. In our study, we propose a new analytical approach for assessing the risk of preterm delivery using EMG recordings which firstly employs Empirical Mode Decomposition (EMD) to obtain their Intrinsic Mode Functions (IMF). Next, the entropy values of both instantaneous amplitude and instantaneous frequency of the first ten IMF components are computed in order to derive ratios of these two distinct components as features. Discrimination accuracy of this approach compared to those proposed previously was then calculated using six differently representative classifiers. Finally, three different electrode positions were analyzed for their prediction accuracy of preterm delivery in order to establish which uterine EMG recording location was optimal signal data. Overall, our results show a clear improvement in prediction accuracy of preterm delivery risk compared with previous approaches, achieving an impressive maximum AUC value of 0.986 when using signals from an electrode positioned below the navel. In sum, this provides a promising new method for analyzing uterine EMG signals to permit accurate clinical assessment of preterm delivery risk.

The Icelandic 16-electrode electrohysterogram database

External recordings of the electrohysterogram (EHG) can provide new knowledge on uterine electrical activity associated with contractions. Better understanding of the mechanisms underlying labor can contribute to preventing preterm birth which is the main cause of mortality and morbidity in newborns. Promising results using the EHG for labor prediction and other uses in obstetric care are the drivers of this work. This paper presents a database of 122 4-by-4 electrode EHG recordings performed on 45 pregnant women using a standardized recording protocol and a placement guide system. The recordings were performed in Iceland between 2008 and 2010. Of the 45 participants, 32 were measured repeatedly during the same pregnancy and participated in two to seven recordings. Recordings were performed in the third trimester (112 recordings) and during labor (10 recordings). The database includes simultaneously recorded tocographs, annotations of events and obstetric information on participants. The publication of this database enables independent and novel analysis of multi-electrode EHG by the researchers in the field and hopefully development towards new life-saving technology.

Propagation of electrical activity in uterine muscle during pregnancy: a review

The uterine muscle (the myometrium) plays its most evident role during pregnancy, when quiescence is required for adequate nourishment and development of the foetus, and during labour, when forceful contractions are needed to expel the foetus and the other products of conception. The myometrium is composed of smooth muscle cells. Contraction is initiated by the spontaneous generation of electrical activity at the cell level in the form of action potentials. The mechanisms underlying uterine quiescence during pregnancy and electrical activation during labour remain largely unknown; as a consequence, the clinical management of preterm contractions during pregnancy and inefficient uterine contractility during labour remains suboptimal. In an effort to improve clinical management of uterine contractions, research has focused on understanding the propagation properties of the electrical activity of the uterus. Different perspectives have been undertaken, from animal and in vitro experiments up to clinical studies and dedicated methods for non-invasive parameter estimation. A comparison of the results is not straightforward due to the wide range of different approaches reported in the literature. However, previous studies unanimously reveal a unique complexity as compared to other organs in the pattern of uterine electrical activity propagation, which necessarily needs to be taken into consideration for future studies to be conclusive. The aim of this review is to structure current variegated knowledge on the properties of the uterus in terms of pacemaker position, pattern, direction and speed of the electrical activity during pregnancy and labour.

Separating sets of term and pre-term uterine EMG records

The analysis of uterine EMG (electrohysterogram-EHG) records may help solve the problem of predicting pre-term labor. We investigated the adaptive autoregressive (AAR) method to estimate the EHG signal spectrograms and sample entropy, to separate and classify sets of term and pre-term delivery records, using the Term-Preterm EHG Database. The database contains four sets of records divided according to the time of delivery (term or pre-term: ⩾37 or < 37 weeks of gestation, respectively) and according to the time of recording (early or later: before or after the 26th week of gestation, respectively). Using the AAR method the term and pre-term delivery records recorded early can be separated (p = 0.002), as well as all term and pre-term delivery records (p < 0.001). Using the sample entropy, the results showed that all term and pre-term delivery records can be separated (p = 0.022). The spectra of the signals for term delivery records have the tendency of moving to lower frequencies as the time of pregnancy increases. We investigated a few classifiers to classify records between term and pre-term delivery sets. Using median frequency measurements and additional clinical information with the synthetic minority over-sampling technique, the quadratic discriminant analysis classifier achieved a 97% classification accuracy for the records recorded early, and 86% for all records regardless of the time of recording; while for the sample entropy measurements, for the same sets of records, using the support vector machine classifier, the classification accuracies were 80% and 87%, respectively.

Non-invasive electrohysterogram recording using flexible concentric ring electrode

Non-invasive electrohysterogram (EHG) recording could provide valuable information about uterine dynamics. Bipolar EHG has usually been performed using monopolar disposable electrodes. Recently concentric ring electrodes have been used for EHG recordings so as to acquire more localized electrical activity which may be helpful for deducing uterine contraction efficiency. Nevertheless concentric ring electrodes have commonly been implemented in rigid substrates. Therefore they do not adapt to the body surface curvature which may cause discomfort for patients and a poor contact between electrode and skin. The aim of this paper is to examine the feasibility of picking up EHG signals (BC-EHG) using a new flexible tripolar concentric ring (TCR) electrode placed on the abdominal surface, and to compare it with the conventional bipolar recordings. For this purpose, a total of 7 recording sessions were carried out in 7 pregnant women. Each recording implied simultaneous acquisition of one bipolar EHG signal and of two bipolar concentric EHG (BC-EHG) signals using the flexible TCR electrode. Then a set of temporal and spectral parameters was computed from both bipolar EHG and BC-EHG bursts. Experimental results show no noticeable difference in duration and in dominant frequency in Fast Wave High frequency range. Nonetheless, the low frequency content (0.1-0.2 Hz) of BC-EHG records is smaller than that of bipolar record. These results suggest that the new flexible TCR electrode permits to pick up uterine electrical activity and may provide additional information for deducing uterine efficiency.

Empirical mode decomposition applied for non-invasive electrohysterograhic signals denoising

The electrical activity of the uterus, i.e. the electrohysterogram (EHG), is one of the most prominent tool for preterm labour. There is no standard acquisition set up and often the EHG is corrupted with different types of noise: maternal and fetal electrocardiogram (mECG, fECG), electrical activity of the skeletal muscles, movement artifacts, power line interference (PLI) etc. Moreover, some of these noises overlap in frequency domain with the EHG. Thus, simple linear filtering approaches are not adequate. In this paper the empirical mode decomposition (EMD), a simple and data driven method, is proposed for EHG denoising. The method is evaluated on simulated data having different signal to noise ratios (SNRs) obtaining promising results.

Tracking the changes in synchrony of the electrophysiological activity as the uterus approaches labor using magnetomyographic technique

The objective of the study was to perform serial magnetomyographic examinations in order to detect changes in synchrony characteristics of myometrial electrophysiological activity as women approach labor. Of the total of 56 patients recruited, the results of 149 examinations from 29 patients were included in the analysis. The global synchrony across each sensor spread over the abdomen was computed and quantified as synchronization index. The mean and the median value of the global synchrony were computed and correlated with time to active labor from the last recording. Overall, synchrony increased as the patient approached active labor (P = .035). Furthermore, mean synchronization index increased twice as fast in the nonnulliparous group compared to the nulliparous group (P = .039). The changes in synchrony of uterine electrophysiological activity near term could aid in prediction of labor.

Linking myometrial physiology to intrauterine pressure; how tissue-level contractions create uterine contractions of labor

The mechanisms used to coordinate uterine contractions are not known. We develop a new model based on the proposal that there is a maximum distance to which action potentials can propagate in the uterine wall. This establishes "regions", where one action potential burst can rapidly recruit all the tissue. Regions are recruited into an organ-level contraction via a stretch-initiated contraction mechanism (myometrial myogenic response). Each uterine contraction begins with a regional contraction, which slightly increases intrauterine pressure. Higher pressure raises tension throughout the uterine wall, which initiates contractions of more regions and further increases pressure. The positive feedback synchronizes regional contractions into an organ-level contraction. Cellular automaton (CA) simulations are performed with Mathematica. Each "cell" is a region that is assigned an action potential threshold. An anatomy sensitivity factor converts intrauterine pressure to regional tension through the Law of Laplace. A regional contraction occurs when regional tension exceeds regional threshold. Other input variables are: starting and minimum pressure, burst and refractory period durations, enhanced contractile activity during an electrical burst, and reduced activity during the refractory period. Complex patterns of pressure development are seen that mimic the contraction patterns observed in laboring women. Emergent behavior is observed, including global synchronization, multiple pace making regions, and system memory of prior conditions. The complex effects of nifedipine and oxytocin exposure are simulated. The force produced can vary as a nonlinear function of the number of regions. The simulation directly links tissue-level physiology to human labor. The concept of a uterine pacemaker is re-evaluated because pace making activity may occur well before expression of a contraction. We propose a new classification system for biological CAs that parallels the 4-class system of Wolfram. However, instead of classifying the rules, biological CAs should classify the set of input values for the rules that describe the relevant biology.

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

The conduction velocity and propagation patterns of the electrohysterogram (EHG) provide fundamental information on the electrophysiological condition of the uterus. However, the accuracy of these measurements can be impaired by both the poor spatial selectivity and sensitivity to the relative direction of the contraction propagation associated with conventional disc electrodes. Concentric ring electrodes could overcome these limitations. The aim of this study was to examine the feasibility of picking up surface EHG signals using a new flexible tripolar concentric ring electrode (TCRE), and to compare these signals with conventional bipolar recordings. Simultaneous recording of conventional bipolar signals and bipolar concentric EHG (BC-EHG) were carried out on 22 pregnant women. Signal bursts were characterized and compared. No significant differences were found between the channels in either duration or dominant frequency in the Fast Wave High frequency range. Nonetheless, the high pass filtering effect of the BC-EHG recordings gave lower frequency content between 0.1 and 0.2 Hz. Although the BC-EHG signal amplitude was about 5-7 times smaller than that of bipolar recordings, a similar signal-to-noise ratio was obtained. These results suggest that the flexible TCRE is able to pick up uterine electrical activity and could provide additional information for deducing the uterine electrophysiological condition.

Study protocol: PoPE-Prediction of Preterm delivery by Electrohysterography

Background

Traditional methods used for prediction of preterm delivery are subjective and inaccurate. The Electrohysterogram (EHG) and in particular the estimation of the EHG conduction velocity, is a relatively new promising method for detecting imminent preterm delivery. To date the analysis of the conduction velocity has relied on visual inspection of the signals. As a next step towards the introduction of EHG analysis as a clinical tool, we propose an automated method for EHG conduction velocity estimation for both the speed and direction of single spike propagation.

Methods/Design

The study design will be an observational cohort study. 100 pregnant women, gestational age between 23 + 5 and 34 weeks, admitted for threatening preterm labor or preterm prelabor rupture of membranes, will be included. The length of the cervical canal will be measured by transvaginal ultrasound. The EHG will be recorded using 4 electrodes in a fixed configuration. Contractions will be detected by analysis of the EHG and using an estimation of the intra uterine pressure. In the selected contractions, the delays between channels will be estimated by cross-correlation, and subsequently, the average EHG conduction velocity will be derived. Patients will be classified as labor group and non-labor group based on the time between measurement and delivery. The average conduction velocity and cervical length will be compared between the groups. The main study endpoints will be sensitivity, specificity, and area under the ROC curve for delivery within 1,2,4,7, and 14 days from the measurement.

Discussion

In this study, the diagnostic accuracy of EHG conduction velocity analysis will be evaluated for detecting preterm labor. Visual and automatic detection of contractions will be compared. Planar wave propagation will be assumed for the calculation of the CV vector.

Trial registration

Current Controlled Trials ISRCTN07603227.

Prediction of spontaneous preterm delivery in singleton pregnancies: where are we and where are we going? A review of literature

Prematurity is the chief cause of neonatal morbidity and mortality. The objective of this study is to review the different methods for predicting preterm delivery in asymptomatic pregnant women and in situations of threatened preterm delivery. A search of the PubMed/Medline database was carried out for the years 1980-2012. We included studies for predicting preterm birth in asymptomatic and symptomatic patients. Models for predicting preterm delivery based on maternal factors, cervical length and obstetric history in first trimester of pregnancy is a valuable avenue of research. Nevertheless, prediction accuracy still needs to be improved. In the second and third trimesters, routine digital vaginal examination is of no value in asymptomatic women. Echography of the cervix is not useful except in patients with a history of late miscarriage or preterm delivery in order to offer them a preventive treatment. In symptomatic women, the combination of digital vaginal examination, cervical echography and fibronectin gives the best predictive results. Electromyography of the uterus and elastography of the cervix are interesting avenues for future research. Identifying patients at risk of preterm delivery should be considered differently at each stage of pregnancy.

Velocity and directionality of the electrohysterographic signal propagation

OBJECTIVE

The initiation of treatment for women with threatening preterm labor requires effective distinction between true and false labor. The electrohysterogram (EHG) has shown great promise in estimating and classifying uterine activity. However, key issues remain unresolved and no clinically usable method has yet been presented using EHG. Recent studies have focused on the propagation velocity of the EHG signals as a potential discriminator between true and false labor. These studies have estimated the propagation velocity of individual spikes of the EHG signals. We therefore focus on estimating the propagation velocity of the entire EHG burst recorded during a contraction in two dimensions.

STUDY DESIGN

EHG measurements were performed on six women in active labor at term, and a total of 35 contractions were used for the estimation of propagation velocity. The measurements were performed using a 16-channel two-dimensional electrode grid. The estimates were calculated with a maximum-likelihood approach.

RESULTS

The estimated average propagation velocity was 2.18 (±0.68) cm/s. No single preferred direction of propagation was found.

CONCLUSION

The propagation velocities estimated in this study are similar to those reported in other studies but with a smaller intra- and inter-patient variation. Thus a potential tool has been established for further studies on true and false labor contractions.

Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.

Automated conduction velocity analysis in the electrohysterogram for prediction of imminent delivery: a preliminary study

Background. Analysis of the electrohysterogram (EHG) is a promising diagnostic tool for preterm delivery. For the introduction in the clinical practice, analysis of the EHG should be reliable and automated to guarantee reproducibility. Study Goal. Investigating the feasibility of automated analysis of the EHG conduction velocity (CV) for detecting imminent delivery. Materials and Methods. Twenty-two patients presenting with uterine contractions (7 preterm) were included. An EHG was obtained noninvasively using a 64-channel high-density electrode grid. Contractions were selected based on the estimated intrauterine pressure derived from the EHG, the tocodynamometer, and maternal perception. Within the selected contractions, the CV vector was identified in two dimensions. Results. Nine patients delivered within 24 hours and were classified as a labor group. 64 contractions were analyzed; the average amplitude of the CV vector was significantly higher for the labor group, 8.65 cm/s ± 1.90, compared to the nonlabor group, 5.30 cm/s ± 1.47 (P < 0.01). Conclusion. The amplitude of the CV is a promising parameter for predicting imminent (preterm) delivery. Automated estimation of this parameter from the EHG signal is feasible and should be regarded as an important prerequisite for future clinical studies and applications.

Comparison of different EHG feature selection methods for the detection of preterm labor

Numerous types of linear and nonlinear features have been extracted from the electrohysterogram (EHG) in order to classify labor and pregnancy contractions. As a result, the number of available features is now very large. The goal of this study is to reduce the number of features by selecting only the relevant ones which are useful for solving the classification problem. This paper presents three methods for feature subset selection that can be applied to choose the best subsets for classifying labor and pregnancy contractions: an algorithm using the Jeffrey divergence (JD) distance, a sequential forward selection (SFS) algorithm, and a binary particle swarm optimization (BPSO) algorithm. The two last methods are based on a classifier and were tested with three types of classifiers. These methods have allowed us to identify common features which are relevant for contraction classification.

Prediction of preterm deliveries from EHG signals using machine learning

There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography), could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term). The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial classifier.

Windowed multivariate autoregressive model improving classification of labor vs. pregnancy contractions

Analyzing the propagation of uterine electrical activity is poised to become a powerful tool in labor detection and for the prediction of preterm labor. Several methods have been proposed to investigate the relationship between signals recorded externally from several sites on the pregnant uterus. A promising recent method is the multivariate autoregressive (MVAR) model. In this paper we proposed a windowed (time varying) version of the multivariate autoregressive model, called W-MVAR, to investigate the connectivity between signals while still respecting their non-stationary characteristics. The proposed method was tested on synthetic signals as well as applied to real signals. The comparison between the two methods on synthetic signals showed the superiority of W-MVAR to detect connectivity even if it is non-stationary. The application of W-MVAR on multichannel real uterine signals show that the proposed method is a good tool to distinguish non-labor and labor signals. These results are very promising and can very possibly have important clinical applications in labor detection and preterm labor prediction.

Effect of an oxytocin receptor antagonist (atosiban) on uterine electrical activity

OBJECTIVE

The purpose of this study was to investigate the effect of atosiban (Tractocile; Ferring, Limhamn, Sweden), an oxytocin receptor antagonist, on uterine electrical activity in women with preterm labor and to determine whether this information can assist in the prediction of preterm delivery.

STUDY DESIGN

Uterine electrical activity was recorded prospectively in 21 women with preterm labor before and during treatment with Tractocile and, for purpose of comparison, in 4 pregnant women without uterine contractions to set the baseline of uterine electrical activity in a quiescent uterus. Uterine activity was recorded with a noninvasive, 9-channel recorder with an electromyography amplifier and a 3-dimensional position sensor with an automatic data analyzer. Uterine electrical activity was quantified by an electrical uterine monitor (EUM) and measured in microwatts per second (μW/s).

RESULTS

The overall pre-Tractocile EUM index was 3.43 ± 0.58 μW/s, which was significantly higher than baseline uterine activity in women without preterm contractions (2.3 ± 0.11 μW/s; P = .001). During the administration of Tractocile, the EUM index gradually decreased in a relatively constant rate from 3.43 ± 0.58 μW/s to 2.56 ± 0.88 μW/s after 330 minutes of continuous therapy (P < .001). The peak effect of Tractocile was observed 4 hours after the initiation of treatment and was followed by a relative plateau. Women with a latency of <7 days from treatment to delivery were characterized by a distinct EUM-pattern in response to Tractocile, compared with women with a latency of ≥7 days (P < .001). A similar EUM-pattern after the administration of Tractocile was also observed for women who delivered at <37 weeks of gestation compared with the women who delivered at term.

CONCLUSION

Tractocile reduces uterine electrical activity in women with preterm labor. This information can provide more insight into the effects of tocolytic agents and to aid in the risk stratification of preterm delivery in women with preterm contractions.

Assessment of parturition with cervical light-induced fluorescence and uterine electromyography

Parturition involves increasing compliance (ripening) of the uterine cervix and activation of the myometrium. These processes take place in a different time frame. Softening and shortening of the cervix starts in midpregnancy, while myometrial activation occurs relatively close to delivery. Methods currently available to clinicians to assess cervical and myometrial changes are subjective and inaccurate, which often causes misjudgments with potentially adverse consequences. The inability to reliably diagnose true preterm labor leads to unnecessary treatments, missed opportunities to improve neonatal outcome, and inherently biased research of treatments. At term, the likelihood of cesarean delivery depends on labor management, which in turn depends on accurate assessments of cervical change and myometrial contractility. Studies from our group and others show that noninvasive measurements of light-induced fluorescence (LIF) of cervical collagen and uterine electromyography (EMG) objectively detect changes in the composition of the cervix and myometrial preparedness to labor and are more reliable than clinical observations alone. We present a conceptual model of parturition constructed on cervical LIF and uterine EMG studies. We also explore how these methodologies could be helpful with managing patients experiencing preterm contractions and with optimizing labor management protocols aimed to reduce cesarean section.

Uterine electromyography for identification of first-stage labor arrest in term nulliparous women with spontaneous onset of labor

OBJECTIVE

We sought to study whether uterine electromyography (EMG) can identify inefficient contractions leading to first-stage labor arrest followed by cesarean delivery in term nulliparous women with spontaneous onset of labor.

STUDY DESIGN

EMG was recorded during spontaneous labor in 119 nulliparous women with singleton term pregnancies in cephalic position. Electrical activity of the myometrium during contractions was characterized by its power density spectrum (PDS).

RESULTS

Mean PDS peak frequency in women undergoing cesarean delivery for first-stage labor arrest was significantly higher (0.55 Hz), than in women delivering vaginally without (0.49 Hz) or with (0.51 Hz) augmentation of labor (P = .001 and P = .01, respectively). Augmentation of labor increased the mean PDS frequency when comparing contractions before and after start of augmentation. This increase was only significant in women eventually delivering vaginally.

CONCLUSION

Contraction characteristics measured by uterine EMG correlate with progression of labor and are influenced by labor augmentation.

Costs of unnecessary admissions and treatments for "threatened preterm labor"

OBJECTIVE

Cervical length (CL) of 3 cm or greater has been shown to have a 97-99% negative predictive value for preterm delivery in women with threatened preterm labor. Consequently, hospitalization and treatment are not indicated in these patients. We analyzed how often patients with a CL of 3 cm or greater are still being admitted and treated for preterm labor and how much this contributes to the economic burden of preterm labor hospitalizations.

STUDY DESIGN

Twelve month hospitalizations for preterm labor at less than 34 weeks at a single institution were reviewed and patients with a CL of 3 cm or greater were identified. We chose to use patients' hospital charges as a surrogate for health care costs, recognizing that charges are not synonymous with the final patient bill and also do not reflect additional costs such as the cost of treatment at the referring facility, transportation, physician fees, and other such costs as lost wages, need for additional child care, etc.

RESULTS

Between July 2009 and June 2010, 139 patients were admitted and treated for preterm labor at our level III center. Fifty of these patients (36%) had a CL of 3 cm or greater. None of them delivered preterm. Total hospital charges for the management of these patients were $1,018 589 (mean, $20,372; median, $14,444).

CONCLUSION

Unnecessary admissions and treatments for threatened preterm labor are part of clinical practice and contribute to exploding health care costs. Using currently available diagnostics, these costs could be lowered significantly without jeopardizing outcome.