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 (4x4 matrix) EHG signals recorded from the women 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.Comment: 4 pages, 3 figures, accepted in the IEEE EMBC conferanc

Assessment of Features between Multichannel Electrohysterogram for Differentiation of Labors

[EN] Electrohysterogram (EHG) is a promising method for noninvasive monitoring of uterine electrical activity. The main purpose of this study was to characterize the multichannel EHG signals to distinguish between term delivery and preterm birth, as well as deliveries within and beyond 24 h. A total of 219 pregnant women were grouped in two ways: (1) term delivery (TD), threatened preterm labor (TPL) with the outcome of preterm birth (TPL_PB), and TPL with the outcome of term delivery (TPL_TD); (2) EHG recording time to delivery (TTD) 24 h. Three bipolar EHG signals were analyzed for the 30 min recording. Six EHG features between multiple channels, including multivariate sample entropy, mutual information, correlation coefficient, coherence, direct partial Granger causality, and direct transfer entropy, were extracted to characterize the coupling and information flow between channels. Significant differences were found for these six features between TPL and TD, and between TTD 24 h. No significant difference was found between TPL_PB and TPL_TD. The results indicated that EHG signals of TD were more regular and synchronized than TPL, and stronger coupling between multichannel EHG signals was exhibited as delivery approaches. In addition, EHG signals propagate downward for the majority of pregnant women regardless of different labors. In conclusion, the coupling and propagation features extracted from multichannel EHG signals could be used to differentiate term delivery and preterm birth and may predict delivery within and beyond 24 h.This research was funded by the National Key R&D Program, grant number 2019YFC0119700, and the National Natural Science Foundation of China, grant number U20A20388.Zhang, Y.; Hao, D.; Yang, L.; Zhou, X.; Ye Lin, Y.; Yang, Y. (2022). Assessment of Features between Multichannel Electrohysterogram for Differentiation of Labors. Sensors. 22(9):1-18. https://doi.org/10.3390/s2209335211822

Uterine contractile efficiency indexes for labor prediction: a bivariate approach from multichannel electrohysterographic records

[EN] Labor prediction is one of the most challenging goals in obstetrics, mainly due to the poor understanding of the factors responsible for the onset of labor. The electrohysterogram (EHG) is the recording of the myoelectrical activity of myometrial cells and has been shown to provide relevant information on the electrophysiological state of the uterus. This information could be used to obtain more accurate labor predictions than those of the currently used techniques, such as the Bishop score, tocography or biochemical markers. Indeed, a number of efforts have already been made to predict labor by this method, separately characterizing the intensity, the coupling degree of the EHG signals and myometrial cell excitability, these being the cornerstones on which contraction efficiency is built. Although EHG characterization can distinguish between different obstetric situations, the reported results have not been shown to provide a practical tool for the clinical detection of true labor. The aim of this work was thus to define and calculate indexes from multichannel EHG recordings related to all the phenomena involved in the efficiency of uterine myoelectrical activity (intensity, excitability and synchronization) and to combine them to form global efficiency indexes (GEI) able to predict delivery in less than 7/14 days. Four EHG synchronization indexes were assessed: linear correlation, the imaginary part of the coherence, phase synchronization and permutation cross mutual information. The results show that even though the synchronization and excitability efficiency indexes can detect increasing trends as labor approaches, they cannot predict labor in less than 7/14 days. However, intensity seems to be the main factor that contributes to myometrial efficiency and is able to predict labor in less than 7/14 days. All the GEls present increasing monotonic trends as pregnancy advances and are able to identify (p < 0.05) patients who will deliver in less than 7/14 days better than single channel and single phenomenon parameters. The GEI based on the permutation cross mutual information shows especially promising results. A simplified EHG recording protocol is proposed here for clinical practice, capable of predicting deliveries in less than 7/14 days, consisting of 4 electrodes vertically aligned with the median line of the uterus. (C) 2018 Elsevier Ltd. All rights reserved.The authors are grateful to Zhenhu Liang, of the Yanshan University, who provided essential information for computing the PLV and NPCMI synchronization indexes. This work was supported by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (DPI2015-68397-R, MINECO/FEDER).Mas-Cabo, J.; Ye Lin, Y.; Garcia-Casado, J.; Alberola Rubio, J.; Perales Marín, AJ.; Prats-Boluda, G. (2018). Uterine contractile efficiency indexes for labor prediction: a bivariate approach from multichannel electrohysterographic records. Biomedical Signal Processing and Control. 46:238-248. https://doi.org/10.1016/j.bspc.2018.07.018S2382484

Characterization of uterine activity by electrohysterography

A growing number of pregnancies is complicated by miscarriage, preterm delivery, and birth defects, with consequent health problems later in life. It is therefore increasingly important to monitor the health status of mother and fetus, so as to permit timely medical intervention when acute health risks are detected. For timely recognition of complications, quantitative assessment of uterine activity can be fundamental during both pregnancy and delivery. During pregnancy, timely prediction of preterm delivery can improve the effectiveness of the required treatments. Unfortunately, the prognostic techniques employed in current obstetrical practice, namely, uterine contraction measurements using an elastic belt (external tocography), cervical change evaluation, and the use of biomarkers like fetal fibronectin, have been demonstrated to be inaccurate for the prediction of preterm delivery. In the last stage of pregnancy and during labor, contractions are routinely and constantly monitored. Especially when complications occur, e.g., when labor shows poor progress, quantitative assessment of uterine activity can guide the physician to choose a uterine contraction induction or augmentation, a cesarean section, or other therapies. Furthermore, monitoring the fetal heart response to the uterine activity (cardiotography) is widely used as a screening test for timely recognition of fetal distress (e.g. asphyxia). However, in current obstetrical practice, accurate quantitative assessment of the uterine contractions can be provided only invasively and during labor. The current golden standard for contraction monitoring, which is based on the direct internal uterine pressure (IUP) measurement by an intrauterine catheter, can be risky and its use is generally limited to very complicated deliveries. The contractile element of the uterus is the myometrium, which is composed of smooth muscle cells. Uterine contractions are caused by electrical activity in the form of action potentials (AP) that propagate through the myometrium cells. Electrohysterography is the measurement of the uterine electrical activity and can be performedby electrodes placed on the abdomen. Electrohysterographic (EHG) measurements are inexpensive and noninvasive. Moreover, it has been demonstrated that the noninvasively recorded EHG signal is representative of those APs that, by propagating from cell to cell, are the root cause of a uterine contraction. Therefore, in view of the limitation of current obstetrical practice, significant benefits could be expected from the introduction of EHG signal analysis for routine contraction monitoring. Previous studies highlighted the potential prognostic and diagnostic value of EHG signal analysis, but did not investigate the possibility of accurately estimating the IUP from noninvasive EHG recordings. Moreover, important issues like the effect of the tissues interposed between the uterus and the skin (volume conductor) on EHG recordings have not been studied. Besides, EHG signal interpretation has been typically based on single-channel measurements, while the use of multiple electrodes conveys additional information (e.g., distribution and dynamics of the electrical activation) that can possibly be predictive of delivery. In this thesis, we focus on the analysis of the EHG signal as an alternative to existing techniques for predicting preterm delivery and monitoring uterine contractions during both pregnancy and delivery. The main goal of this work is to contribute to the technical basis which is required for the introduction of electrohysterography in everyday clinical practice. A major part of this thesis investigates the possibility of using electrohysterography to replace invasive IUP measurements. A novel method for IUP estimation from EHG recordings is developed in the first part of this thesis. The estimates provided by the method are compared to the IUP invasively recorded on women during delivery and result in a root mean squared error (RMSE) with respect to the reference invasive IUP recording as low as 5 mmHg, which is comparable to the accuracy of the invasive golden standard. Another important objective of this thesis work is to contribute to the introduction of novel techniques for timely prediction of preterm delivery. As the spreading of electrical activity at the myometrium is the root cause of coordinated and effective contractions, i.e., contractions that are capable of pushing the fetus down into the birth canal ultimately leading to delivery, a multichannel analysis of the spatial propagation properties of the EHG signal could provide a fundamental contribution for predicting delivery. A thorough study of the EHG signal propagation properties is therefore carried out in this work. Parameters related to the EHG that are potentially predictive of delivery, such as the uterine area where the contraction originates (pacemaker area) or the distribution and dynamics of the EHG propagation vector, can be derived from the delay by which the signal is detected at multiple locations over the whole abdomen. To analyze the propagation of EHG signals on a large scale (cm), a method is designed for calculating the detection delay among the EHG signals recorded by by electrodes placed on the abdomen. Electrohysterographic (EHG) measurements are inexpensive and noninvasive. Moreover, it has been demonstrated that the noninvasively recorded EHG signal is representative of those APs that, by propagating from cell to cell, are the root cause of a uterine contraction. Therefore, in view of the limitation of current obstetrical practice, significant benefits could be expected from the introduction of EHG signal analysis for routine contraction monitoring. Previous studies highlighted the potential prognostic and diagnostic value of EHG signal analysis, but did not investigate the possibility of accurately estimating the IUP from noninvasive EHG recordings. Moreover, important issues like the effect of the tissues interposed between the uterus and the skin (volume conductor) on EHG recordings have not been studied. Besides, EHG signal interpretation has been typically based on single-channel measurements, while the use of multiple electrodes conveys additional information (e.g., distribution and dynamics of the electrical activation) that can possibly be predictive of delivery. In this thesis, we focus on the analysis of the EHG signal as an alternative to existing techniques for predicting preterm delivery and monitoring uterine contractions during both pregnancy and delivery. The main goal of this work is to contribute to the technical basis which is required for the introduction of electrohysterography in everyday clinical practice. A major part of this thesis investigates the possibility of using electrohysterography to replace invasive IUP measurements. A novel method for IUP estimation from EHG recordings is developed in the first part of this thesis. The estimates provided by the method are compared to the IUP invasively recorded on women during delivery and result in a root mean squared error (RMSE) with respect to the reference invasive IUP recording as low as 5 mmHg, which is comparable to the accuracy of the invasive golden standard. Another important objective of this thesis work is to contribute to the introduction of novel techniques for timely prediction of preterm delivery. As the spreading of electrical activity at the myometrium is the root cause of coordinated and effective contractions, i.e., contractions that are capable of pushing the fetus down into the birth canal ultimately leading to delivery, a multichannel analysis of the spatial propagation properties of the EHG signal could provide a fundamental contribution for predicting delivery. A thorough study of the EHG signal propagation properties is therefore carried out in this work. Parameters related to the EHG that are potentially predictive of delivery, such as the uterine area where the contraction originates (pacemaker area) or the distribution and dynamics of the EHG propagation vector, can be derived from the delay by which the signal is detected at multiple locations over the whole abdomen. To analyze the propagation of EHG signals on a large scale (cm), a method is designed for calculating the detection delay among the EHG signals recorded by multiple electrodes. Relative to existing interelectrode delay estimators, this method improves the accuracy of the delay estimates for interelectrode distances larger than 5-10 cm. The use of a large interelectrode distance aims at the assessment of the EHG propagation properties through the whole uterine muscle using a limited number of sensors. The method estimates values of velocity within the physiological range and highlights the upper part of the uterus as the most frequent (65%) pacemaker area during labor. Besides, our study suggests that more insight is needed on the effect that tissues interposed between uterus and skin (volume conductor) have on the EHG signal. With the aim of improving the current interpretation and measurement accuracy of EHG parameters with potential clinical relevance, such as the conduction velocity (CV), a volume conductor model for the EHG signal is introduced and validated. The intracellular AP at the myometrium is analytically modeled in the spatial domain by a 2-parameter exponential in the form of a Gamma variate function. The unknown atomical parameters of the volume conductor model are the thicknesses of the biological tissues interposed between the uterus and the abdominal surface. These model parameters can be measured by echography for validation. The EHG signal is recorded by an electrode matrix on women with contractions. In order to increase the spatial resolution of the EHG measurements and reduce the geometrical and electrical differences among the tissues below the recording locations, electrodes with a reduced surface and smaller interelectrode distance are needed relative to the previous studies on electrohysterography. The EHG signal is recorded, for the first time, by a 64-channel (8×8) high-density electrode grid, comprising 1 mm diameter electrodes with 4 mm interelectrode distance. The model parameters are estimated in the spatial frequency domain from the recorded EHG signal by a least mean square method. The model is validated by comparing the thickness of the biological tissues recorded by echography to the values estimated using the mathematical model. The agreement between the two measures (RMSE = 1 mm and correlation coefficient, R = 0.94) suggests the model to be representative of the underlying physiology. In the last part of this dissertation, the analysis of the EHG signal propagation focuses on the CV estimation of single APs. As on a large scale this parameter cannot be accurately derived, the propagation analysis is here carried out on a small scale (mm). Also for this analysis, the EHG signal is therefore recorded by a 3×3 cm2 high-density electrode grid containing 64 electrodes (8×8). A new method based on maximum likelihood estimation is then applied in two spatial dimensions to provide an accurate estimate of amplitude and direction of the AP CV. Simulation results prove the proposed method to be more robust to noise than the standard techniques used for other electrophysiological signals, leading to over 56% improvement of the RMS CV estimate accuracy. Furthermore, values of CV between 2 cm/s and 12 cm/s, which are in agreement with invasive and in-vitro measurements described in the literature, are obtained from real measurements on ten women in labor. In conclusion, this research provides a quantitative characterization of uterine contractions by EHG signal analysis. Based on an extensive validation, this thesis indicates that uterine contractions can be accurately monitored noninvasively by dedicated analysis of the EHG signal. Furthermore, our results open the way to new clinical studies and applications aimed at improving the understanding of the electrophysiological mechanisms leading to labor, possibly reducing the incidence of preterm delivery and improving the perinatal outcome

A Machine Learning System for Automatic Detection of Preterm Activity Using Artificial Neural Networks and Uterine Electromyography Data

Preterm births are babies born before 37 weeks of gestation. The premature delivery of babies is a major global health issue with those affected at greater risk of developing short and long-term complications. Therefore, a better understanding of why preterm births occur is needed. Electromyography is used to capture electrical activity in the uterus to help treat and understand the condition, which is time consuming and expensive. This has led to a recent interest in automated detection of the electromyography correlates of preterm activity. This paper explores this idea further using artificial neural networks to classify term and preterm records, using an open dataset containing 300 records of uterine electromyography signals. Our approach shows an improvement on existing studies with 94.56% for sensitivity, 87.83% for specificity, and 94% for the area under the curve with 9% global error when using the multilayer perceptron neural network trained using the Levenberg-Marquardt algorithm

Dynamic neural network architecture inspired by the immune algorithm to predict preterm deliveries in pregnant women

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 is most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. There is a strong body of evidence emerging that suggests the analysis of uterine electrical signals, from the abdominal surface (Electrohysterography – EHG), could provide a viable way of diagnosing true labour and even predict preterm deliveries. This paper explores this idea further and presents a new dynamic self-organized network immune algorithm that classifies term and preterm records, using an open dataset containing 300 records (38 preterm and 262 term). Using the dataset, oversampling and cross validation techniques are evaluated against other similar studies. The proposed approach shows an improvement on existing studies with 89% sensitivity, 91% specificity, 90% positive predicted value, 90% negative predicted value, and an overall accuracy of 90%

Analysis of the propagation of uterine electrical activity applied to predict preterm labor

There are many open questions concerning the functioning of the human uterus. One of these open questions concerns exactly how the uterus operates as an organ to perform the very organized act of contracting in a synchronized fashion to expulse a new human into this world. If we don‟t understand how it works when it is working normally, it is obvious that we will not be as capable of intervening or preventing when, sometimes with tragic consequences, it does not do its job properly and a child is born before it is ready. The aim of our research is to be able to understand what the electrical activity of the uterus can tell us about the risk of premature birth, to understand better how the uterus works and to benefit from these understanding to find tool that can be used for labor detection and prediction of preterm labor. This idea of using the externally detected electrical activity of the uterus (electrohysterogram or EHG) to predict preterm labor is not new and lot of work has already been put into it. The novel approach in this work is not to use the signal collected from one or two isolated places on the expectant mother‟s abdomen but to map the propagation of the signals and to investigate the auto organization of the contractions. We therefore use a matrix of electrodes to give us a much more complete picture of the organization and operation of the uterus as pregnancy reaches its conclusion. Labor is the physiologic process by which a fetus is expelled from the uterus to the outside world and is defined as regular uterine contractions accompanied by cervical effacement and dilatation. In the normal labor, the uterine contractions and cervix dilatation are preceded by biochemical changes in the cervical connective tissue.Il reste beaucoup de questions ouvertes concernant le fonctionnement de l'utérus humain. L'une de ces questions est comment l'utérus fonctionne en tant qu‟organe organisé pour générer une contraction synchrone et expulser un nouvel être humain dans ce monde ? Si nous ne comprenons pas comment l‟utérus fonctionne, quand il fonctionne normalement, il est évident que nous ne serons pas en mesure d'intervenir ou de prévoir quand, avec parfois des conséquences tragiques, il ne fait pas son travail correctement et qu‟un enfant nait avant d‟être prêt ! Le but de notre recherche est de comprendre ce que l'activité électrique de l'utérus peut nous apporter sur la prévention du risque de naissance prématurée, de mieux comprendre comment fonctionne l'utérus et de bénéficier de ces connaissances pour développer un outil qui peut être utilisé pour la détection de l‟accouchement et la prédiction du travail prématuré. Cette idée d'utiliser l'activité électrique détectée à la surface de l‟abdomen (ou électrohystérogramme EHG) pour prédire un accouchement prématuré n'est pas nouvelle et beaucoup de travaux ont déjà été mis en oeuvre. La nouvelle approche dans ce travail n‟est pas d‟utiliser le signal recueilli par un ou deux endroits isolés sur l'abdomen de la future mère, mais de cartographier la propagation des signaux et d‟explorer l'auto organisation des contractions. Nous utilisons donc une matrice d'électrodes pour nous donner une image beaucoup plus complète de l'organisation et du fonctionnement de l'utérus. L‟accouchement est le processus physiologique par lequel le foetus est expulsé de l'utérus vers le monde extérieur. Il est défini comme la survenue de contractions utérines régulières accompagnées de l'effacement du col et de la dilatation cervicale. Dans le travail normal, les contractions de l'utérus et la dilatation du col sont précédées par des changements biochimiques du tissu conjonctif du col utérin

Etude de la propagation de l‟activité électrique utérine dans une optique clinique : Application a la détection des menaces d‟accouchement prématuré

Uterine contractions are essentially controlled by two physiological phenomena: cell excitability and propagation of uterine electrical activity probably related to high and low frequencies of uterine electromyogram, called electrohysterogram -EHG-, respectively. All previous studies have been focused on extracting parameters from the high frequency part and did not show a satisfied potential for clinical application. The objective of this thesis is the analysis of the propagation EHG signals of during pregnancy and labor in the view of extracting tool for clinical application. A novelty of our thesis is the multichannel recordings by using 4x4 electrodes matrix posed on the woman abdomen. Monovariate analysis was aimed to investigate the nonlinear characteristics of EHG signals. Bivariate and multivariate analyses have been done to analyze the propagation of the EHG signals by detecting the connectivity between the signals. An increase of the nonlinearity associated by amplitude synchronization and phase desynchronization were detected. Results indicate a highest EHG propagation during labor than pregnancy and an increase of this propagation with the week of gestations. The results show the high potential of propagation‟s parameters in clinical point of view such as labor detection and then preterm labor prediction. We proposed novel combination of Blind Source Separation and empirical mode decomposition to denoise monopolar EHG as a possible way to increase the classification rate of pregnancy and labor.Les contractions utérines sont contrôlées par deux phénomènes physiologiques: l'excitabilité cellulaire et la propagation de l'activité électrique utérine probablement liées aux hautes et basses fréquences de l‟electrohysterograme (EHG) respectivement. Toutes les études précédentes ont porté sur l'extraction de paramètres de la partie haute fréquence et n'ont pas montré un potentiel satisfait pour l'application clinique. L'objectif de cette thèse est l'analyse de propagation de l'EHG pendant la grossesse et le travail dans la vue de l'extraction des outils pour une application clinique. Une des nouveautés de la thèse est l‟enregistrement multicanaux à l'aide d‟une matrice d'électrodes 4x4 posée sur l'abdomen de la femme. Analyse monovariés visait à étudier les caractéristiques non linéaires des signaux EHG, analyses bivariées et multivariées ont été effectuées pour analyser la propagation des signaux EHG par la détection de la connectivité entre les signaux. Une augmentation de la non- linéarité associée par une synchronisation en amplitude et de désynchronisation en phase a été détectée. Les résultats indiquent plus de propagation au cours du travail que la grossesse et une augmentation de cette propagation avec les semaines de gestations. Les résultats montrent le potentiel élevé de paramètres de propagation dans le point de vue clinique tel que la détection du travail et de prédiction du travail prématuré. Finalement, nous avons proposé une nouvelle combinaison entre Séparation Aveugles de Sources et la Décomposition en Modes Empiriques pour débruiter les signaux EHG monopolaires comme un moyen possible d'augmenter le taux de classification de signaux grossesse et l'accouchement

Etude de la propagation de l’activité électrique utérine dans une optique clinique: Application à la détection des menaces d’accouchement prématuré.

Uterine contractions are essentially controlled by two physiological phenomena: cell excitability and propagation of uterine electrical activity probably related to high and low frequencies of uterine electromyogram, called electrohysterogram -EHG-, respectively. All previous studies have been focused on extracting parameters from the high frequency part and did not show a satisfied potential for clinical application. The objective of this thesis is the analysis of the propagation EHG signals of during pregnancy and labor in the view of extracting tool for clinical application. A novelty of our thesis is the multichannel recordings by using 4x4 electrodes matrix posed on the woman abdomen. Monovariate analysis was aimed to investigate the nonlinear characteristics of EHG signals. Bivariate and multivariate analyses have been done to analyze the propagation of the EHG signals by detecting the connectivity between the signals. An increase of the nonlinearity associated by amplitude synchronization and phase desynchronization were detected. Results indicate a highest EHG propagation during labor than pregnancy and an increase of this propagation with the week of gestations. The results show the high potential of propagation’s parameters in clinical point of view such as labor detection and then preterm labor prediction. We proposed novel combination of Blind Source Separation and empirical mode decomposition to denoise monopolar EHG as a possible way to increase the classification rate of pregnancy and labor.Les contractions utérines sont contrôlées par deux phénomènes physiologiques: l'excitabilité cellulaire et la propagation de l'activité électrique utérine probablement liées aux hautes et basses fréquences de l’electrohysterograme (EHG) respectivement. Toutes les études précédentes ont porté sur l'extraction de paramètres de la partie haute fréquence et n'ont pas montré un potentiel satisfait pour l'application clinique. L'objectif de cette thèse est l'analyse de propagation de l'EHG pendant la grossesse et le travail dans la vue de l'extraction des outils pour une application clinique. Une des nouveautés de la thèse est l’enregistrement multicanaux à l'aide d’une matrice d'électrodes 4x4 posée sur l'abdomen de la femme. Analyse monovariés visait à étudier les caractéristiques non linéaires des signaux EHG, analyses bivariées et multivariées ont été effectuées pour analyser la propagation des signaux EHG par la détection de la connectivité entre les signaux. Une augmentation de la non-linéarité associée par une synchronisation en amplitude et de désynchronisation en phase a été détectée. Les résultats indiquent plus de propagation au cours du travail que la grossesse et une augmentation de cette propagation avec les semaines de gestations. Les résultats montrent le potentiel élevé de paramètres de propagation dans le point de vue clinique tel que la détection du travail et de prédiction du travail prématuré. Finalement, nous avons proposé une nouvelle combinaison entre Séparation Aveugles de Sources et la Décomposition en Modes Empiriques pour débruiter les signaux EHG monopolaires comme un moyen possible d'augmenter le taux de classification de signaux grossesse et l'accouchement