Quantitative analysis of contraction patterns in electrical activity signal of pregnant uterus as an alternative to mechanical approach

Evaluation of the accuracy of a low-cost external tocodynamometer in a pilot study in Malawi

Uterine contraction monitoring during labor has been linked to improved maternal outcomes. However, performing this monitoring can be challenging for financial and logistical reasons in low resource settings. This proof-of-concept study aimed to compare the accuracy of a low cost external tocodynamometer we developed to that of a commercially available external tocodynamometer. In total, 60 patients with anticipated vaginal deliveries at a hospital in Blantyre, Malawi were enrolled. Both the research device and the commercial device were secured to the patients, and traces were recorded simultaneously from each device. Trace pairs were split into 10 minute segments, and contraction locations were independently annotated on a selection of 75 contemporaneous trace pairs from 38 out of 60 patients by two expert clinicians. In total, 484 contractions were marked on the research device, and 465 contractions were marked on the commercially available device, 312 of which were marked consistently on both devices. The average consistency of marked contractions on the same device between the two observers was 0.89 for the research device compared with 0.84 for the commercially available device. The average consistency between the two devices using a 10-patient rolling average increased from 0.50 at the beginning of the study to 0.64 at the end. The annotated traces from the two devices suggested the same clinical management 72% of the time. The research device displayed reasonable agreement with the commercially available tocodynamometer in detecting contractions. The increase in the measured consistency over the course of the study suggests that improving usability of the device to ensure better positioning on the patient could result in improved performance. Further studies assessing the accuracy and usability of the device are needed.

Characteristics of phase synchronization in electrohysterography and tocodynamometry for preterm birth prediction

Preterm birth prediction is important in prenatal care; however, it remains a significant challenge due to the complex physiological mechanisms involved. This study aimed to explore the feasibility of phase synchronization of multiple oscillatory components across electrohysterography (EHG) and tocodynamometry (TOCO) signals to identify preterm births using advanced machine-learning techniques. Using an open-access EHG dataset, we first assessed the degree of phase synchronization of five specified frequency ranges from 0.08 to 5.0 Hz in three individual EHG signals by constructing two distinct sets of mean phase coherence: the inclusion or exclusion of TOCO signals. We then employed two machine-learning models, XGBoost and TabNet, to classify preterm and term delivery conditions and analyze the predictive potential of these features. The models' performance was evaluated by considering varying lengths of time windows and the use of overlapping windows. Our results demonstrate the importance of lower-frequency EHG signals and synchronization patterns across the horizontal plane of the abdomen, particularly synchronization between the upper and lower regions of the uterus. Furthermore, we observed a distinctive pattern in the high-frequency band (1.0-2.2 Hz), emphasizing the important role of the lower horizontal regions with other sites in the synchronization process. Interestingly, our findings indicated that TOCO signals, while not substantially enhancing the overall prediction performance, contributed to slightly improved accuracy rates when combined with EHG signals. This study suggests the critical role of EHG signals and their intricate spatiotemporal patterns in predicting preterm birth, providing insights for the development of more accurate and efficient prediction models.

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.

Regional identification of information flow termination of electrohysterographic signals: Towards understanding human uterine electrical propagation

BACKGROUND AND OBJECTIVE

The uterine electrohysterogram (EHG) contains important information about electrical signal propagation which may be useful to monitor and predict the progress of pregnancy towards parturition. Directed information processing has the potential to be of use in studying EHG recordings. However, so far, there is no directed information-based estimation scheme that has been applied to investigating the propagation of human EHG recordings. To realize this, the approach of directed information and its reliability and adaptability should be scientifically studied.

METHODS

We demonstrated an estimation scheme of directed information to identify the spatiotemporal relationship between the recording channels of EHG signal and assess the algorithm reliability initially using simulated data. Further, a regional identification of information flow termination (RIIFT) approach was developed and applied for the first time to extant multichannel EHG signals to reveal the terminal zone of propagation of the electrical activity associated with uterine contraction. RIIFT operates by estimating the pairwise directed information between neighboring EHG channels and identifying the location where there is the strongest inward flow of information. The method was then applied to publicly-available experimental data obtained from pregnant women with the use of electrodes arranged in a 4-by-4 grid.

RESULTS

Our results are consistent with the suggestions from the previous studies with the added identification of preferential sites of excitation termination - within the estimated area, the direction of surface action potential propagation towards the medial axis of uterus during contraction was discovered for 72.15% of the total cases, demonstrating that our RIIFT method is a potential tool to investigate EHG propagation for advancing our understanding human uterine excitability.

CONCLUSIONS

We developed a new approach and applied it to multichannel human EHG recordings to investigate the electrical signal propagation involved in uterine contraction. This provides an important platform for future studies to fill knowledge gaps in the spatiotemporal patterns of electrical excitation of the human uterus.

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).

IDENTIFICATION OF UTERINE CONTRACTIONS BY AN ENSEMBLE OF GAUSSIAN PROCESSES

Identifying uterine contractions with the aid of machine learning methods is necessary vis-á-vis their use in combination with fetal heart rates and other clinical data for the assessment of a fetus wellbeing. In this paper, we study contraction identification by processing noisy signals due to uterine activities. We propose a complete four-step method where we address the imbalanced classification problem with an ensemble Gaussian process classifier, where the Gaussian process latent variable model is used as a decision-maker. The results of both simulation and real data show promising performance compared to existing methods.

Electrodes in external electrohysterography: a systematic literature review

BACKGROUND

In low-income countries, pregnant women do not have easy access to health care, especially in rural and peri-urban areas. In this context, they can be surprised by the uterine contractions that precede childbirth and sometimes find themselves giving birth at home or on the way to the nearest health facility (located miles away from their home). In view of the development of an external uterine electrohysterogram acquisition system for labour prediction, a review of the literature on electrodes and their characteristics is necessary.

METHODS

A comprehensive literature review was conducted to collate information on the use of electrodes in external EHG recording and their characteristics.

RESULTS

Wet electrodes based on Ag/AgCl redox chemistry are the most common type of electrodes for EHG, employed in different configurations on the pregnant woman's abdomen. All positioning configurations are around the vertical median axis if they are not placed directly on it. Positioning below the navel seems to be the most efficient. The number of source, reference, and ground electrodes used varies from one author to another, as does the distance between the electrodes.

CONCLUSION

Two well-positioned source electrodes on the vertical median axis, with ground electrode on the right side of the hip and reference one on the left side, are able to generate a good external EHG recording signal. The minimum allowed inter-electrode distance is approximately 17.5 to 25mm.

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.

Propagation of spontaneous electrical activity in the ex vivo human uterus

Contractions of the non-pregnant uterus play a key role in fertility. Yet, the electrophysiology underlying these contractions is poorly understood. In this paper, we investigate the presence of uterine electrical activity and characterize its propagation in unstimulated ex vivo human uteri. Multichannel electrohysterographic measurements were performed in five freshly resected human uteri starting immediately after hysterectomy. Using an electrode grid externally and an electrode array internally, measurements were performed up to 24 h after hysterectomy and compared with control. Up to 2 h after hysterectomy, we measured biopotentials in all included uteri. The median root mean squared (RMS) values of the external measurements ranged between 3.95 μV (interquartile range (IQR) 2.41–14.18 μV) and 39.4 μV (interquartile range (IQR) 10.84–105.64 μV) and were all significantly higher than control (median RMS of 1.69 μV, IQR 1.13–3.11 μV), consisting of chicken breast meat. The RMS values decreased significantly over time. After 24 h, the median RMS (1.27 μV, IQR 0.86–3.04 μV) was comparable with the control (1.69 μV, IQR 1.13–3.11 μV, p = 0.125). The internal measurements showed a comparable pattern over time, but overall lower amplitude. The measured biopotentials propagated over the uterine surface, following both a plane-wave as well as an erratic pattern. No clear pacemaker location nor a preferred propagation direction could be identified. These results show that ex vivo uteri can spontaneously generate propagating biopotentials and provide novel insight contributing to improving our understanding of the electrophysiology of the human non-pregnant uterus.

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.

Acquisition and Analysis of Electrohysterogram Signal

Electrohysterogram (EHG) signal is the signal related to action potentials propagating through smooth muscle cells of the uterus (myometrium) to the abdomen of pregnant women which is also known as uterine contraction signal. Cardiotocography (CTG) is the most common method used for monitoring fetal heart rate (FHR) and uterine contractions during pregnancy and labor. This method detects mechanical activity of fetal heart and uterus, however, it provides low accuracy and sensibility and hence more accurate methods are required. The abdominal electrode method of FECG monitoring and Electrohysterography (EHG) are alternative noninvasive method to monitor the FHR and uterine contractions during pregnancy which provides better results compared to CTG. Each information such as the frequency of uterine contractions, length of the contraction and contraction power of uterus, indicates the condition of the uterus which will help the obstetricians to identify the progress of labor. All these above mentioned parameters can be identified from the EHG signal acquired non-invasively by placing the electrodes on the abdomen of the pregnant women. In this work the acquisition of EHG signal as well as analysis of EHG signal in both antepartum condition and labor condition have been carried out and parameters such as number of contractions, contraction duration, amplitude, power of contraction are computed and the quantitative analysis of EHG signals in both above mentioned conditions are performed and it is compared with the simultaneously recorded uterine contraction signal parameters from Cardiotocography (CTG).

Automatic Identification and Classification of Fetal Heart-Rate Decelerations from Cardiotocographic Recordings

Cardiotocography (CTG) consists in the simultaneous recording of two distinct traces, the fetal heart rate (FHR; bpm) and the maternal uterine contractions (UCs; mmHg). CTG analysis consists in the evaluation of specific features of traces, among which fetal decelerations (DECs) are considered the "center-stage" since possibly related to fetal distress. DECs are classified based on their duration and occurrence in relation to UCs as prolonged, early, late and variable; each class associates to a specific status of the fetus health. Typically, CTG traces are visually interpreted; however, computerized CTG analysis may overcome subjectivity in CTG interpretation. Thus, this study proposes a new automatic algorithm for computerized identification and classification of DECs. The algorithm was tested on the 552 CTG recordings constituting the "CTU-CHB intra-partum CTG database" of Physionet. Of these, 470 (85.15%) were found suitable for automatic DECs identification and classification. Overall, 5888 DECs were identified, of which 3255 (55.28%) were classified while the other 2633 (44.72%) remained unclassified due to very strict preliminary classification criteria (now required for avoiding misclassifications). Among the classified DECs, 468 (14.38%) were classified as prolonged, 1498 (46.02%) as early, 32 (0.98%) as late, 1257 (38.62%) as variable. Thus, among the classified DECs, the most common are the early and the variable ones (overall 84.64%), the occurrence of which ranged from 0 to 14 DECs per recording. These findings are in agreement with what reported in literature. In conclusion, the proposed algorithm for automatic DECs identification and classification represents a useful tool for computerized CTG analysis.

New electrohysterogram-based estimators of intrauterine pressure signal, tonus and contraction peak for non-invasive labor monitoring

BACKGROUND

Uterine activity monitoring is an essential part of managing the progress of pregnancy and labor. Although intrauterine pressure (IUP) is the only reliable method of estimating uterine mechanical activity, it is highly invasive. Since there is a direct relationship between the electrical and mechanical activity of uterine cells, surface electrohysterography (EHG) has become a noninvasive monitoring alternative. The Teager energy (TE) operator of the EHG signal has been used for IUP continuous pressure estimation, although its accuracy could be improved. We aimed to develop new optimized IUP estimation models for clinical application.

APPROACH

We first considered enhancing the optimal estimation of IUP clinical features (maximum pressure and tonus) rather than optimizing the signal only (continuous pressure). An adaptive algorithm was also developed to deal with inter-patient variability. For each optimizing signal feature (continuous pressure, maximum pressure and tonus), individual (single patient), global (full database) and adaptive models were built to estimate the recorded IUP signal. The results were evaluated by computing the root mean square errors (RMSe): continuous pressure error (CPe), maximum pressure error (MPe) and tonus error (TOe).

MAIN RESULTS

The continuous pressure global model yielded IUP estimates with Cpe  =  14.61 mm Hg, MPe  =  29.17 mm Hg and Toe  =  7.8 mm Hg. The adaptive models significantly reduced errors to CPe  =  11.88, MPe  =  16.02 and Toe  =  5.61 mm Hg. The EHG-based IUP estimates outperformed those from traditional tocographic recordings, which had significantly higher errors (CPe  =  21.93, MPe  =  26.97, and TOe  =  13.96).

SIGNIFICANCE

Our results show that adaptive models yield better IUP estimates than the traditional approaches and provide the best balance of the different errors computed for a better assessment of the labor progress and maternal and fetal well-being.

Application of decision tree in determining the importance of surface electrohysterography signal characteristics for recognizing uterine contractions

The aims of this study were to apply decision tree to classify uterine activities (contractions and non-contractions) using the waveform characteristics derived from different channels of electrohysterogram (EHG) signals and then rank the importance of these characteristics. Both the tocodynamometer (TOCO) and 8-channel EHG signals were simultaneously recorded from 34 healthy pregnant women within 24 h before delivery. After preprocessing of EHG signals, EHG segments corresponding to the uterine contractions and non-contractions were manually extracted from both original and normalized EHG signals according to the TOCO signals and the human marks. 24 waveform characteristics of the EHG segments were derived separately from each channel to train the decision tree and classify the uterine activities. The results showed the Power and sample entropy (SamEn) extracted from the un-normalized EHG segments played the most important roles in recognizing uterine activities. In addition, the EHG signal characteristics from channel 1 produced better classification results (AUC = 0.75, Sensitivity = 0.84, Specificity = 0.78, Accuracy = 0.81) than the others. In conclusion, decision tree could be used to classify the uterine activities, and the Power and SamEn of un-normalized EHG segments were the most important characteristics in uterine contraction classification.

Clinical Use of Electrohysterography During Term Labor: A Systematic Review on Diagnostic Value, Advantages, and Limitations

Importance

Real-time electrohysterography (EHG)-based technologies have recently become available for uterine monitoring during term labor. Therefore, obstetricians need to be familiar with the diagnostic value, advantages, and limitations of using EHG.

Objective

The aims of this study were to determine the diagnostic value of EHG in comparison to (1) the intrauterine pressure catheter (IUPC), (2) the external tocodynamometer (TOCO), and (3) in case of maternal obesity; (4) to evaluate EHG from users' and patients' perspectives; and (5) to assess whether EHG can predict labor outcome.

Evidence Acquisition

A systematic review was performed in the MEDLINE, EMBASE, and Cochrane library in October 2017 resulting in 209 eligible records, of which 20 were included.

Results

A high sensitivity for contraction detection was achieved by EHG (range, 86.0%-98.0%), which was significantly better than TOCO (range, 46.0%-73.6%). Electrohysterography also enhanced external monitoring in case of maternal obesity. The contraction frequency detected by EHG was on average 0.3 to 0.9 per 10 minutes higher compared with IUPC, which resulted in a positive predictive value of 78.7% to 92.0%. When comparing EHG tocograms with IUPC traces, an underestimation of the amplitude existed despite that patient-specific EHG amplitudes have been mitigated by amplitude normalization. Obstetricians evaluated EHG tocograms as better interpretable and more adequate than TOCO. Finally, potential EHG parameters that could predict a vaginal delivery were a predominant fundal direction and a lower peak frequency.

Conclusions and Relevance

Electrohysterography enhances external uterine monitoring of both nonobese and obese women. Obstetricians consider EHG as better interpretable; however, they need to be aware of the higher contraction frequency detected by EHG and of the amplitude mismatch with intrauterine pressure measurements.

Characterization and automatic classification of preterm and term uterine records

Predicting preterm birth is uncertain, and numerous scientists are searching for non-invasive methods to improve its predictability. Current researches are based on the analysis of ElectroHysteroGram (EHG) records, which contain information about the electrophysiological properties of the uterine muscle and uterine contractions. Since pregnancy is a long process, we decided to also characterize, for the first time, non-contraction intervals (dummy intervals) of the uterine records, i.e., EHG signals accompanied by a simultaneously recorded external tocogram measuring mechanical uterine activity (TOCO signal). For this purpose, we developed a new set of uterine records, TPEHGT DS, containing preterm and term uterine records of pregnant women, and uterine records of non-pregnant women. We quantitatively characterized contraction intervals (contractions) and dummy intervals of the uterine records of the TPEHGT DS in terms of the normalized power spectra of the EHG and TOCO signals, and developed a new method for predicting preterm birth. The results on the characterization revealed that the peak amplitudes of the normalized power spectra of the EHG and TOCO signals of the contraction and dummy intervals in the frequency band 1.0-2.2 Hz, describing the electrical and mechanical activity of the uterus due to the maternal heart (maternal heart rate), are high only during term pregnancies, when the delivery is still far away; and they are low when the delivery is close. However, these peak amplitudes are also low during preterm pregnancies, when the delivery is still supposed to be far away (thus suggesting the danger of preterm birth); and they are also low or barely present for non-pregnant women. We propose the values of the peak amplitudes of the normalized power spectra due to the influence of the maternal heart, in an electro-mechanical sense, in the frequency band 1.0-2.2 Hz as a new biophysical marker for the preliminary, or early, assessment of the danger of preterm birth. The classification of preterm and term, contraction and dummy intervals of the TPEHGT DS, for the task of the automatic prediction of preterm birth, using sample entropy, the median frequency of the power spectra, and the peak amplitude of the normalized power spectra, revealed that the dummy intervals provide quite comparable and slightly higher classification performances than these features obtained from the contraction intervals. This result suggests a novel and simple clinical technique, not necessarily to seek contraction intervals but using the dummy intervals, for the early assessment of the danger of preterm birth. Using the publicly available TPEHG DB database to predict preterm birth in terms of classifying between preterm and term EHG records, the proposed method outperformed all currently existing methods. The achieved classification accuracy was 100% for early records, recorded around the 23rd week of pregnancy; and 96.33%, the area under the curve of 99.44%, for all records of the database. Since the proposed method is capable of using the dummy intervals with high classification accuracy, it is also suitable for clinical use very early during pregnancy, around the 23rd week of pregnancy, when contractions may or may not be present.

Could electrohysterography be the solution for external uterine monitoring in obese women?

OBJECTIVE

To evaluate the influence of maternal obesity on the performance of external tocodynamometry and electrohysterography.

STUDY DESIGN

In a 2-hour measurement during term labor, uterine contractions were simultaneously measured by electrohysterography, external tocodynamometry, and intra-uterine pressure catheter. The sensitivity was compared between groups based on obesity (non-obese/obese/morbidly obese) or uterine palpation (good/moderate/poor), and was correlated to maternal BMI and abdominal circumference.

RESULT

We included 14 morbidly obese, 18 obese, and 20 non-obese women. In morbidly obese women, the median sensitivity was 87.2% (IQR 74-93) by electrohysterography and 45.0% (IQR 36-66) by external tocodynamometry (p < 0.001). The sensitivity of electrohysterography appeared to be non-influenced by obesity category (p = 0.279) and uterine palpation (p = 0.451), while the sensitivity of tocodynamometry decreased significantly (p = 0.005 and p < 0.001, respectively). Furthermore, the sensitivity of both external methods was negatively correlated with obesity parameters, being non-significant for electrohysterography (range p-values 0.057-0.088) and significant for external tocodynamometry (all p-values < 0.001).

CONCLUSIONS

Electrohysterography performs significantly better than external tocodynamometry in case of maternal obesity.

Feasibility of Transabdominal Electrohysterography for Analysis of Uterine Activity in Nonpregnant Women

PURPOSE

Uterine activity plays a key role in reproduction, and altered patterns of uterine contractility have been associated with important physiopathological conditions, such as subfertility, dysmenorrhea, and endometriosis. However, there is currently no method to objectively quantify uterine contractility outside pregnancy without interfering with the spontaneous contraction pattern. Transabdominal electrohysterography has great potential as a clinical tool to characterize noninvasively uterine activity, but results of this technique in nonpregnant women are poorly documented. The purpose of this study is to investigate the feasibility of transabdominal electrohysterography in nonpregnant women.

METHODS

Longitudinal measurements were performed on 22 healthy women in 4 representative phases of the menstrual cycle. Twelve electrohysterogram-based indicators previously validated in pregnancy have been estimated and compared in the 4 phases of the cycle. Using the Tukey honest significance test, significant differences were defined for P values below .05.

RESULTS

Half of the selected electrohysterogram-based indicators showed significant differences between menses and at least 1 of the other 3 phases, that is the luteal phase.

CONCLUSION

Our results suggest transabdominal electrohysterography to be feasible for analysis of uterine activity in nonpregnant women. Due to the lack of a golden standard, this feasibility study is indirectly validated based on physiological observations. However, these promising results motivate further research aiming at evaluating electrohysterography as a method to improve understanding and management of dysfunctions (possibly) related to altered uterine contractility, such as infertility, endometriosis, and dysmenorrhea.

Comparison of electrohysterogram signal measured by surface electrodes with different designs: A computational study with dipole band and abdomen models

Non-invasive measurement of uterine activity using electrohysterogram (EHG) surface electrodes has been attempted to monitor uterine contraction. This study aimed to computationally compare the performance of acquiring EHG signals using monopolar electrode and three types of Laplacian concentric ring electrodes (bipolar, quasi-bipolar and tri-polar). With the implementation of dipole band model and abdomen model, the performances of four electrodes in terms of the local sensitivity were quantified by potential attenuation. Furthermore, the effects of fat and muscle thickness on potential attenuation were evaluated using the bipolar and tri-polar electrodes with different radius. The results showed that all the four types of electrodes detected the simulated EHG signals with consistency. That the bipolar and tri-polar electrodes had greater attenuations than the others, and the shorter distance between the origin and location of dipole band at 20 dB attenuation, indicating that they had relatively better local sensitivity. In addition, ANOVA analysis showed that, for all the electrodes with different outer ring radius, the effects of fat and muscle on potential attenuation were significant (all p < 0.01). It is therefore concluded that the bipolar and tri-polar electrodes had higher local sensitivity than the others, indicating that they can be applied to detect EHG effectively.

Comparison of electrohysterogram characteristics during uterine contraction and non-contraction during labor

Uterine contraction is one of the most important indication in the labor progression. Electrohysterogram (EHG) is a promising method for monitoring uterine contraction and discriminating efficient and inefficient contractions. This study aims to analyze the difference of EHG signals between two groups. EHG signals are recorded with abdominal electrodes from 20 pregnant women, including 10 in term labor group and 10 in non-labor group. Typical linear and nonlinear characteristics of EHG signals, including root mean square (RMS), peak frequency (PF), median frequency (MDF), mean frequency (MNF), parameters from wavelet decomposition (W4, W5) and time reversibility (Tr) are extracted. These characteristics are compared between contraction and non-contraction in term labor group and non-labor group. The result shows that RMS, W4 and W5 of contraction are significantly larger than non-contraction both within term labor group and between two groups (all p<;0.001). However, MDF and MNF are significantly smaller (all p<;0.05). Furthermore, all characteristics of non-contraction show no significant difference between two groups, except MNF. The variability of RMS, W4, W5 and Tr of contraction are significantly larger than non-contraction both within term labor group and between two groups (all p<;0.05, with p<;0.001 for W5 and Tr). However, the variability of MDF, PF and MNF are significantly smaller (all p<;0.05). Moreover, the variability of all characteristics of non-contraction shows no significant difference between two groups, except MNF. We have shown that characteristics of EHG signals and their variability during contraction are quite different from non-contraction. Therefore, it is feasible to separate uterine contractions and monitor uterine activity with EHG signals.

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.

Comparison of the onset of uterine contractions determined from tocodynamometry and maternal perception

The aim of this study was to investigate the time difference (TD) between the onset of uterine contraction (UC) determined from tocodynamometry (TOCO) and identified by maternal perception. The online available Icelandic database was used to calculate TD, which was defined as the difference between when it was felt by a pregnant woman and the starting point on the UC signal recorded by a TOCO. A total of 295 TDs from 78 recordings (from a total of 33 participants; among them, 13 participants included at least 3 recordings from different gestational weeks) were analyzed with the overall mean±SD of TD calculated. For each individual participant with at least 3 recordings, regression analysis was then performed to investigate the relationship between the mean TD from each recording with gestational week, with their overall slope calculated. The results showed that 85.4% of TDs was within [-40, 40] s, with an overall mean TD of 3.04 s (p>0.05), indicating that there was no significant difference between the UC onset determined from TOCO and maternal perception. It was also noticed that 61.5% recordings (48 out of 78 recordings) had all positive or negative TD for all the UCs analyzed within a recording. Furthermore, the regression analysis showed that the regression line slope was negative for 10 out of the 13 participants with at least 3 recordings from different gestational weeks, resulting in that the overall slope (-2.85±5.58) was significantly negative (p<;0.05), and indicating that UC onset TD decreased with gestational weeks. In summary, this study quantitatively investigated the TD between the onset of UCs determined from TOCO and maternal perception, providing scientific evidence for future studies to understand the underlying mechanism of the time sequence of UC activity determined from different techniques.

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.

Toward a new modality for detecting a uterine rupture: electrohysterogram propagation analysis during trial of labor after cesarean

OBJECTIVE

Observational cohort study which aimed to explore the potential of electrohysterogram (EHG) analysis for detecting a uterine rupture during trial of labor after cesarean. The EHG propagation characteristics surrounding the uterine scar of six patients with a previous cesarean section were compared to a control group of five patients without a scarred uterus.

METHODS

The EHG was recorded during the first stage of labor using a high-resolution 64-channel electrode grid positioned on the maternal abdomen across the cesarean scar. Based on simulations, the inter-channel correlation and propagation direction were adopted as EHG parameters for evaluating possible disruption of electrical propagation by the uterine scar.

RESULTS

No significant differences in inter-channel correlation or propagation direction were observed between the group of patients with an intact uterine scar and the control group. A strong predominance of vertical propagation was observed in one case, in which scar rupture occurred.

CONCLUSIONS

The results support unaffected propagation of electrical activity through the intact uterine scar tissue suggesting that changes in the EHG might only occur in case of rupture.

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.

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.

Low-complexity intrauterine pressure estimation using the Teager energy operator on electrohysterographic recordings

Monitoring the progression of maternal uterine activity provides important prognostic information during pregnancy and parturition. Currently used methods for intrauterine pressure (IUP) measurement are unsuitable for long-term observation of uterine activity. The abdominally measured electrohysterogram (EHG) provides a non-invasive alternative to the existing methods for long-term ambulatory uterine contraction monitoring. A new low-complexity method for IUP estimation based on the Teager energy (TE) operator is proposed. The TE operator was used as it mimics the physiologic phenomena underlying the generation of the EHG signals. Several EHG signal analysis methods for IUP estimation from the literature are compared with the new TE method. The comparison is based on correlation and root mean square error of the IUP estimate with the gold standard internally measured IUP as well as their respective computational complexity. The proposed method results in a superior IUP estimation accuracy and complexity compared to state-of-the-art methods from the literature, with a complexity as much as 55 times lower. Therefore, the proposed method offers a valuable new option for long-term ambulatory uterine monitoring.

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.

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.

Monitoring uterine activity during labor: a comparison of 3 methods

OBJECTIVE

Tocodynamometry (Toco; strain gauge technology) provides contraction frequency and approximate duration of labor contractions but suffers frequent signal dropout, necessitating repositioning by a nurse, and may fail in obese patients. The alternative invasive intrauterine pressure catheter (IUPC) is more reliable and adds contraction pressure information but requires ruptured membranes and introduces small risks of infection and abruption. Electrohysterography (EHG) reports the electrical activity of the uterus through electrodes placed on the maternal abdomen. This study compared all 3 methods of contraction detection simultaneously in laboring women.

STUDY DESIGN

Upon consent, laboring women were monitored simultaneously with Toco, EHG, and IUPC. Contraction curves were generated in real-time for the EHG, and all 3 curves were stored electronically. A contraction detection algorithm was used to compare frequency and timing between methods. Seventy-three subjects were enrolled in the study; 14 were excluded due to hardware failure of 1 or more of the devices (n = 12) or inadequate data collection duration (n = 2).

RESULTS

In comparison with the gold-standard IUPC, EHG performed significantly better than Toco with regard to the Contractions Consistency Index (CCI). The mean CCI for EHG was 0.88 ± 0.17 compared with 0.69 ± 0.27 for Toco (P < .0001). In contrast to Toco, EHG was not significantly affected by obesity.

CONCLUSION

Toco does not correlate well with the gold-standard IUPC and fails more frequently in obese patients. EHG provides a reliable noninvasive alternative, regardless of body habitus.

Use of uterine electromyography to diagnose term and preterm labor

Current methodologies to assess the process of labor, such as tocodynamometry or intrauterine pressure catheters, fetal fibronectin, cervical length measurement and digital cervical examination, have several major drawbacks. They only measure the onset of labor indirectly and do not detect cellular changes characteristic of true labor. Consequently, their predictive values for term or preterm delivery are poor. Uterine contractions are a result of the electrical activity within the myometrium. Measurement of uterine electromyography (EMG) has been shown to detect contractions as accurately as the currently used methods. In addition, changes in cell excitability and coupling required for effective contractions that lead to delivery are reflected in changes of several EMG parameters. Use of uterine EMG can help to identify patients in true labor better than any other method presently employed in the clinic.

Noninvasive estimation of the electrohysterographic action-potential conduction velocity

Electrophysiological monitoring of the fetal-heart and the uterine-muscle activity, referred to as an electrohysterogram, is essential to permit timely treatment during pregnancy. While remarkable progress is reported for fetal-cardiac-activity monitoring, the electrohysterographic (EHG) measurement and interpretation remain challenging. In particular, little attention has been paid to the analysis of the EHG propagation, whose characteristics might be predictive of the preterm delivery. Therefore, this paper focuses, for the first time, on the noninvasive estimation of the conduction velocity of the EHG-action potentials. To this end, multichannel EHG recording and surface high-density electrodes are used. A maximum-likelihood method is employed for analyzing the EHG-action-potential propagation in two dimensions. The use of different weighting strategies of the derived cost function is introduced to deal with the poor signal similarity between different channels. The presented methods were evaluated by specific simulations proving the best weighting strategy to lead to an accuracy improvement of 56.7%. EHG measurements on ten women with uterine contractions confirmed the feasibility of the method by leading to conduction velocity values within the expected physiological range.

Myometrium electromechanical modeling for internal uterine pressure estimation by electrohysterography

During delivery, quantitative information on the uterine activity can be provided by internal uterine pressure (IUP) recordings using an invasive intrauterine pressure catheter (IUPC). The electrohysterogram, which measures the electrical signal that drives the mechanical contraction of the uterine muscle and the consequent IUP increase, is recorded by electrodes placed on the abdomen. Recent work demonstrated the possibility of reliably estimating the IUP noninvasively by electrohysterographic (EHG) signal analysis. To further improve the accuracy of IUP estimates, we investigated the use of three nonlinear functions for modeling the relationship between the electrical activation measured by the EHG signal and the mechanical response of the uterine muscle. The feature employed for obtaining a first estimate of the IUP is the unnormalized first statistical moment of the EHG spectrum. The relationship between the extracted feature and the IUP is modeled by a second-order polynomial, a logarithmic, and an exponential function. For validation, the IUPC and the EHG signals were recorded on nine women in labor. A second-order polynomial model already provided estimates that are highly correlated with the IUPC signal (r = 0.73). However, the logarithmic model resulted to be the most accurate, especially in terms of root mean squared error (RMSE = 5.13 mmHg).