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Robust Characterization of the Uterine Myoelectrical Activity in Different Obstetric Scenarios

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Robust Characterization of the Uterine Myoelectrical Activity in Different Obstetric Scenarios

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dc.contributor.author Mas-Cabo, Javier es_ES
dc.contributor.author Ye Lin, Yiyao es_ES
dc.contributor.author Garcia-Casado, Javier es_ES
dc.contributor.author Díaz-Martínez, María del Alba es_ES
dc.contributor.author Perales-Marin, Alfredo es_ES
dc.contributor.author Monfort-Ortiz, Rogelio es_ES
dc.contributor.author Roca-Prats, Alba es_ES
dc.contributor.author Lopez-Corral, Angel es_ES
dc.contributor.author Prats-Boluda, Gema es_ES
dc.date.accessioned 2020-12-18T04:31:59Z
dc.date.available 2020-12-18T04:31:59Z
dc.date.issued 2020-07-05 es_ES
dc.identifier.issn 1099-4300 es_ES
dc.identifier.uri http://hdl.handle.net/10251/157365
dc.description.abstract [EN] Electrohysterography (EHG) has been shown to provide relevant information on uterine activity and could be used for predicting preterm labor and identifying other maternal fetal risks. The extraction of high-quality robust features is a key factor in achieving satisfactory prediction systems from EHG. Temporal, spectral, and non-linear EHG parameters have been computed to characterize EHG signals, sometimes obtaining controversial results, especially for non-linear parameters. The goal of this work was to assess the performance of EHG parameters in identifying those robust enough for uterine electrophysiological characterization. EHG signals were picked up in different obstetric scenarios: antepartum, including women who delivered on term, labor, and post-partum. The results revealed that the 10th and 90th percentiles, for parameters with falling and rising trends as labor approaches, respectively, differentiate between these obstetric scenarios better than median analysis window values. Root-mean-square amplitude, spectral decile 3, and spectral moment ratio showed consistent tendencies for the different obstetric scenarios as well as non-linear parameters: Lempel-Ziv, sample entropy, spectral entropy, and SD1/SD2 when computed in the fast wave high bandwidth. These findings would make it possible to extract high quality and robust EHG features to improve computer-aided assessment tools for pregnancy, labor, and postpartum progress and identify maternal fetal risks. es_ES
dc.description.sponsorship This work was supported by the Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund (MCIU/AEI/FEDER, UE RTI2018-094449-A-I00-AR) and the Generalitat Valenciana (AICO/2019/220 & GV/2018/104) es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Entropy es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Electrohysterogram (EHG) es_ES
dc.subject Myoelectric uterine activity es_ES
dc.subject Postpartum es_ES
dc.subject Spectral content es_ES
dc.subject Sample entropy es_ES
dc.subject Spectral entropy es_ES
dc.subject Lempel Ziv es_ES
dc.subject Time-reversibility es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Robust Characterization of the Uterine Myoelectrical Activity in Different Obstetric Scenarios es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/e22070743 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//GV%2F2018%2F104/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094449-A-I00/ES/ELECTROHISTEROGRAFIA PARA LA MEJORA EN LA TOMA DE DECISIONES EN SITUACIONES DE RIESGO EN OBSTETRICIA: PARTO PREMATURO E INDUCCION DEL PARTO/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//AICO%2F2019%2F220/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Servicio de Alumnado - Servei d'Alumnat es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Mas-Cabo, J.; Ye Lin, Y.; Garcia-Casado, J.; Díaz-Martínez, MDA.; Perales-Marin, A.; Monfort-Ortiz, R.; Roca-Prats, A.... (2020). Robust Characterization of the Uterine Myoelectrical Activity in Different Obstetric Scenarios. Entropy. 22(7):1-15. https://doi.org/10.3390/e22070743 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/e22070743 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 15 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 22 es_ES
dc.description.issue 7 es_ES
dc.identifier.pmid 33286515 es_ES
dc.identifier.pmcid PMC7517284 es_ES
dc.relation.pasarela S\415113 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.description.references Wagura, P., Wasunna, A., Laving, A., Wamalwa, D., & Ng’ang’a, P. (2018). Prevalence and factors associated with preterm birth at kenyatta national hospital. BMC Pregnancy and Childbirth, 18(1). doi:10.1186/s12884-018-1740-2 es_ES
dc.description.references Liu, L., Johnson, H. L., Cousens, S., Perin, J., Scott, S., Lawn, J. E., … Black, R. E. (2012). Global, regional, and national causes of child mortality: an updated systematic analysis for 2010 with time trends since 2000. The Lancet, 379(9832), 2151-2161. doi:10.1016/s0140-6736(12)60560-1 es_ES
dc.description.references Howson, C. P., Kinney, M. V., McDougall, L., & Lawn, J. E. (2013). Born Too Soon: Preterm birth matters. Reproductive Health, 10(S1). doi:10.1186/1742-4755-10-s1-s1 es_ES
dc.description.references Euliano, T. Y., Nguyen, M. T., Darmanjian, S., McGorray, S. P., Euliano, N., Onkala, A., & Gregg, A. R. (2013). Monitoring uterine activity during labor: a comparison of 3 methods. American Journal of Obstetrics and Gynecology, 208(1), 66.e1-66.e6. doi:10.1016/j.ajog.2012.10.873 es_ES
dc.description.references Devedeux, D., Marque, C., Mansour, S., Germain, G., & Duchêne, J. (1993). Uterine electromyography: A critical review. American Journal of Obstetrics and Gynecology, 169(6), 1636-1653. doi:10.1016/0002-9378(93)90456-s es_ES
dc.description.references Chkeir, A., Fleury, M.-J., Karlsson, B., Hassan, M., & Marque, C. (2013). Patterns of electrical activity synchronization in the pregnant rat uterus. BioMedicine, 3(3), 140-144. doi:10.1016/j.biomed.2013.04.007 es_ES
dc.description.references Fele-Žorž, G., Kavšek, G., Novak-Antolič, Ž., & Jager, F. (2008). A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups. Medical & Biological Engineering & Computing, 46(9), 911-922. doi:10.1007/s11517-008-0350-y es_ES
dc.description.references Mas-Cabo, J., Prats-Boluda, G., Perales, A., Garcia-Casado, J., Alberola-Rubio, J., & Ye-Lin, Y. (2018). Uterine electromyography for discrimination of labor imminence in women with threatened preterm labor under tocolytic treatment. Medical & Biological Engineering & Computing, 57(2), 401-411. doi:10.1007/s11517-018-1888-y es_ES
dc.description.references Vinken, M. P. G. C., Rabotti, C., Mischi, M., & Oei, S. G. (2009). Accuracy of Frequency-Related Parameters of the Electrohysterogram for Predicting Preterm Delivery. Obstetrical & Gynecological Survey, 64(8), 529-541. doi:10.1097/ogx.0b013e3181a8c6b1 es_ES
dc.description.references Hassan, M., Terrien, J., Marque, C., & Karlsson, B. (2011). Comparison between approximate entropy, correntropy and time reversibility: Application to uterine electromyogram signals. Medical Engineering & Physics, 33(8), 980-986. doi:10.1016/j.medengphy.2011.03.010 es_ES
dc.description.references Lemancewicz, A., Borowska, M., Kuć, P., Jasińska, E., Laudański, P., Laudański, T., & Oczeretko, E. (2016). Early diagnosis of threatened premature labor by electrohysterographic recordings – The use of digital signal processing. Biocybernetics and Biomedical Engineering, 36(1), 302-307. doi:10.1016/j.bbe.2015.11.005 es_ES
dc.description.references Garcia-Casado, J., Ye-Lin, Y., Prats-Boluda, G., Mas-Cabo, J., Alberola-Rubio, J., & Perales, A. (2018). Electrohysterography in the diagnosis of preterm birth: a review. Physiological Measurement, 39(2), 02TR01. doi:10.1088/1361-6579/aaad56 es_ES
dc.description.references Most, O., Langer, O., Kerner, R., Ben David, G., & Calderon, I. (2008). Can myometrial electrical activity identify patients in preterm labor? American Journal of Obstetrics and Gynecology, 199(4), 378.e1-378.e6. doi:10.1016/j.ajog.2008.08.003 es_ES
dc.description.references Verdenik, I., Pajntar, M., & Leskošek, B. (2001). Uterine electrical activity as predictor of preterm birth in women with preterm contractions. European Journal of Obstetrics & Gynecology and Reproductive Biology, 95(2), 149-153. doi:10.1016/s0301-2115(00)00418-8 es_ES
dc.description.references Horoba, K., Jezewski, J., Matonia, A., Wrobel, J., Czabanski, R., & Jezewski, M. (2016). Early predicting a risk of preterm labour by analysis of antepartum electrohysterograhic signals. Biocybernetics and Biomedical Engineering, 36(4), 574-583. doi:10.1016/j.bbe.2016.06.004 es_ES
dc.description.references Lucovnik, M., Maner, W. L., Chambliss, L. R., Blumrick, R., Balducci, J., Novak-Antolic, Z., & Garfield, R. E. (2011). Noninvasive uterine electromyography for prediction of preterm delivery. American Journal of Obstetrics and Gynecology, 204(3), 228.e1-228.e10. doi:10.1016/j.ajog.2010.09.024 es_ES
dc.description.references Smrdel, A., & Jager, F. (2015). Separating sets of term and pre-term uterine EMG records. Physiological Measurement, 36(2), 341-355. doi:10.1088/0967-3334/36/2/341 es_ES
dc.description.references Maner, W. (2003). Predicting term and preterm delivery with transabdominal uterine electromyography. Obstetrics & Gynecology, 101(6), 1254-1260. doi:10.1016/s0029-7844(03)00341-7 es_ES
dc.description.references Leman, H., Marque, C., & Gondry, J. (1999). Use of the electrohysterogram signal for characterization of contractions during pregnancy. IEEE Transactions on Biomedical Engineering, 46(10), 1222-1229. doi:10.1109/10.790499 es_ES
dc.description.references Mischi, M., Chen, C., Ignatenko, T., de Lau, H., Ding, B., Oei, S. G. G., & Rabotti, C. (2018). Dedicated Entropy Measures for Early Assessment of Pregnancy Progression From Single-Channel Electrohysterography. IEEE Transactions on Biomedical Engineering, 65(4), 875-884. doi:10.1109/tbme.2017.2723933 es_ES
dc.description.references Garfield, R. E., Maner, W. L., MacKay, L. B., Schlembach, D., & Saade, G. R. (2005). Comparing uterine electromyography activity of antepartum patients versus term labor patients. American Journal of Obstetrics and Gynecology, 193(1), 23-29. doi:10.1016/j.ajog.2005.01.050 es_ES
dc.description.references Maner, W. L., & Garfield, R. E. (2007). Identification of Human Term and Preterm Labor using Artificial Neural Networks on Uterine Electromyography Data. Annals of Biomedical Engineering, 35(3), 465-473. doi:10.1007/s10439-006-9248-8 es_ES
dc.description.references DIMITROV, G. V., ARABADZHIEV, T. I., MILEVA, K. N., BOWTELL, J. L., CRICHTON, N., & DIMITROVA, N. A. (2006). Muscle Fatigue during Dynamic Contractions Assessed by New Spectral Indices. Medicine & Science in Sports & Exercise, 38(11), 1971-1979. doi:10.1249/01.mss.0000233794.31659.6d es_ES
dc.description.references Nagarajan, R., Eswaran, H., Wilson, J. D., Murphy, P., Lowery, C., & Preißl, H. (2003). Analysis of uterine contractions: a dynamical approach. The Journal of Maternal-Fetal & Neonatal Medicine, 14(1), 8-21. doi:10.1080/jmf.14.1.8.21 es_ES
dc.description.references Zhang, X.-S., Roy, R. J., & Jensen, E. W. (2001). EEG complexity as a measure of depth of anesthesia for patients. IEEE Transactions on Biomedical Engineering, 48(12), 1424-1433. doi:10.1109/10.966601 es_ES
dc.description.references Garfield, R. E., Maner, W. L., Maul, H., & Saade, G. R. (2005). Use of uterine EMG and cervical LIF in monitoring pregnant patients. BJOG: An International Journal of Obstetrics & Gynaecology, 112, 103-108. doi:10.1111/j.1471-0528.2005.00596.x es_ES
dc.description.references Grotegut, C. A., Paglia, M. J., Johnson, L. N. C., Thames, B., & James, A. H. (2011). Oxytocin exposure during labor among women with postpartum hemorrhage secondary to uterine atony. American Journal of Obstetrics and Gynecology, 204(1), 56.e1-56.e6. doi:10.1016/j.ajog.2010.08.023 es_ES


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