{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T22:20:26Z","timestamp":1773613226337,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T00:00:00Z","timestamp":1602201600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","award":["PEst- UID\/EEA\/00066\/2019"],"award-info":[{"award-number":["PEst- UID\/EEA\/00066\/2019"]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","award":["UID\/MAT\/04561\/2019."],"award-info":[{"award-number":["UID\/MAT\/04561\/2019."]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia and NMT, S.A.","award":["PD\/BDE\/150312\/2019."],"award-info":[{"award-number":["PD\/BDE\/150312\/2019."]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>Electrohysterography (EHG) is a promising technique for pregnancy monitoring and preterm risk evaluation. It allows for uterine contraction monitoring as early as the 20th gestational week, and it is a non-invasive technique based on recording the electric signal of the uterine muscle activity from electrodes located in the abdominal surface. In this work, EHG-based contraction detection methodologies are applied using signal envelope features. Automatic contraction detection is an important step for the development of unsupervised pregnancy monitoring systems based on EHG. The exploratory methodologies include wavelet energy, Teager energy, root mean square (RMS), squared RMS, and Hilbert envelope. In this work, two main features were evaluated: contraction detection and its related delineation accuracy. The squared RMS produced the best contraction (97.15 \u00b1 4.66%) and delineation (89.43 \u00b1 8.10%) accuracy and the lowest false positive rate (0.63%). Despite the wavelet energy method having a contraction accuracy (92.28%) below the first-rated method, its standard deviation was the second best (6.66%). The average false positive rate ranged between 0.63% and 4.74%\u2014a remarkably low value.<\/jats:p>","DOI":"10.3390\/app10207014","type":"journal-article","created":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T10:19:23Z","timestamp":1602238763000},"page":"7014","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Automatic Contraction Detection Using Uterine Electromyography"],"prefix":"10.3390","volume":"10","author":[{"given":"Filipa","family":"Esgalhado","sequence":"first","affiliation":[{"name":"NOVA School of Science and Technology, NOVA University Lisbon, 2829-516 Caparica, Portugal"},{"name":"NMT, S.A., Parque Tecnol\u00f3gico de Cantanhede, N\u00facleo 04, Lote 3, 3060-197 Cantanhede, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2287-4265","authenticated-orcid":false,"given":"Arnaldo G.","family":"Batista","sequence":"additional","affiliation":[{"name":"NOVA School of Science and Technology, NOVA University Lisbon, 2829-516 Caparica, Portugal"},{"name":"Center of Technology and Systems\u2014UNINOVA, NOVA School of Science and Technology\u2014NOVA University Lisbon, 2829-516 Caparica, Portugal"}]},{"given":"Helena","family":"Mouri\u00f1o","sequence":"additional","affiliation":[{"name":"Faculdade de Ci\u00eancias, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal"}]},{"given":"Sara","family":"Russo","sequence":"additional","affiliation":[{"name":"NOVA School of Science and Technology, NOVA University Lisbon, 2829-516 Caparica, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8103-8574","authenticated-orcid":false,"given":"Catarina R. Palma","family":"dos Reis","sequence":"additional","affiliation":[{"name":"Maternidade Alfredo da Costa, Rua Viriato 1, 1050-170 Lisboa, Portugal"},{"name":"Nova Medical School, Faculty of Medical Sciences, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal"}]},{"given":"F\u00e1tima","family":"Serrano","sequence":"additional","affiliation":[{"name":"Maternidade Alfredo da Costa, Rua Viriato 1, 1050-170 Lisboa, Portugal"},{"name":"Nova Medical School, Faculty of Medical Sciences, Universidade Nova de Lisboa, 1169-056 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7913-7047","authenticated-orcid":false,"given":"Valentina","family":"Vassilenko","sequence":"additional","affiliation":[{"name":"NOVA School of Science and Technology, NOVA University Lisbon, 2829-516 Caparica, Portugal"},{"name":"NMT, S.A., Parque Tecnol\u00f3gico de Cantanhede, N\u00facleo 04, Lote 3, 3060-197 Cantanhede, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4270-3284","authenticated-orcid":false,"given":"Manuel","family":"Duarte Ortigueira","sequence":"additional","affiliation":[{"name":"NOVA School of Science and Technology, NOVA University Lisbon, 2829-516 Caparica, Portugal"},{"name":"Center of Technology and Systems\u2014UNINOVA, NOVA School of Science and Technology\u2014NOVA University Lisbon, 2829-516 Caparica, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2020,10,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1736","DOI":"10.1016\/j.medengphy.2013.07.008","article-title":"Comparison of non-invasive electrohysterographic recording techniques for monitoring uterine dynamics","volume":"35","author":"Valero","year":"2013","journal-title":"Med. Eng. Phys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1367","DOI":"10.3109\/14767058.2014.954539","article-title":"A comparison between electrical uterine monitor, tocodynamometer and intra uterine pressure catheter for uterine activity in labor","volume":"28","author":"Hadar","year":"2015","journal-title":"J. Matern. Neonatal Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1016\/j.bbe.2016.08.005","article-title":"Automated detection of uterine contractions in tocography signals\u2013Comparison of algorithms","volume":"36","author":"Horoba","year":"2016","journal-title":"Biocybern. Biomed. Eng."},{"key":"ref_4","first-page":"190","article-title":"The normal and abnormal contractile waves of the uterus during labour","volume":"138","author":"Alvarez","year":"1954","journal-title":"Gynaecologia"},{"key":"ref_5","unstructured":"Auger, F., Flandrin, P., Gon\u00e7alves, P., and Lemoine, O. (1995). Time-Frequency Toolbox Reference Guide, Rice University."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1016\/j.ajog.2012.03.019","article-title":"A new method for assessing uterine activity: Haran et al","volume":"206","author":"Macones","year":"2012","journal-title":"Am. J. Obstet. Gynecol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"193","DOI":"10.4236\/jbise.2010.32025","article-title":"Classification of non stationary signals using multiscale decomposition","volume":"3","author":"Chendeb","year":"2010","journal-title":"J. Biomed. Sci. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1636","DOI":"10.1016\/0002-9378(93)90456-S","article-title":"Uterine electromyography: A critical review","volume":"169","author":"Devedeux","year":"1993","journal-title":"Am. J. Obstet. Gynecol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"911","DOI":"10.1007\/s11517-008-0350-y","article-title":"A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups","volume":"46","author":"Jager","year":"2008","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1038\/s41372-018-0065-3","article-title":"Could electrohysterography be the solution for external uterine monitoring in obese women?","volume":"38","author":"Vlemminx","year":"2018","journal-title":"J. Perinatol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"692","DOI":"10.1016\/j.tjog.2015.05.005","article-title":"Effect of obesity on preterm delivery prediction by transabdominal recording of uterine electromyography","volume":"55","author":"Lucovnik","year":"2016","journal-title":"Taiwan. J. Obstet. Gynecol."},{"key":"ref_12","unstructured":"Diab, A. (2015). Study of the Nonlinear Properties and Propagation Characteristics of the Uterine Electrical Activity during Pregnancy and Labor. [Ph.D. Thesis, Universit\u00e9 de Technologie de Compi\u00e8gne]."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Zaylaa, A., Diab, A., Khalil, M., and Marque, C. (2017, January 19\u201321). Multichannel EHG segmentation for automatically identifying contractions and motion artifacts. Proceedings of the 2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME), Beirut, Lebanon.","DOI":"10.1109\/ICABME.2017.8167563"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Rabotti, C., Mischi, M., van Laar, J.O.E.H., Oei, S.G., and Bergmans, J.W.M. (2009, January 3\u20136). Myometrium electromechanical modeling for internal uterine pressure estimation by electrohysterography. Proceedings of the 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, MN, USA.","DOI":"10.1109\/IEMBS.2009.5332397"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1111\/aogs.12818","article-title":"Uterine electromyography during active phase compared with latent phase of labor at term","volume":"95","author":"Bregar","year":"2016","journal-title":"Acta Obstet. Gynecol. Scand."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1085\/jgp.80.3.353","article-title":"Improved electrical coupling in uterine smooth muscle is associated with increased numbers of gap junctions at parturition","volume":"80","author":"Sims","year":"1982","journal-title":"J. Gen. Physiol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"C130","DOI":"10.1152\/ajpcell.1989.256.1.C130","article-title":"Improved propagation in myometrium associated with gap junctions during parturition","volume":"256","author":"Miller","year":"1989","journal-title":"Am. J. Physiol. Physiol."},{"key":"ref_18","unstructured":"Verhoeff, A. (1985). Myometrial Contractility and Gap junCtions: An Experimental Study in Chronically Instrumented Ewes, Erasmus University Rotterdam."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1016\/S0002-9378(98)70443-0","article-title":"Gap junction currents in cultured muscle cells from human myometrium","volume":"178","author":"Miyoshi","year":"1998","journal-title":"Am. J. Obstet. Gynecol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1109\/10.844224","article-title":"Uterine EMG analysis: A dynamic approach for change detection and classification","volume":"47","author":"Khalil","year":"2000","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/S0222-0776(00)88906-3","article-title":"Surveillance des grossesses \u00e0 risque par \u00e9lectromyographie ut\u00e9rine","volume":"17","author":"Marque","year":"1995","journal-title":"RBM-News"},{"key":"ref_22","unstructured":"Horoba, K., Jezewski, J., Wrobel, J., and Graczyk, S. (2001, January 25\u201328). Algorithm for detection of uterine contractions from electrohysterogram. Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Istanbul, Turkey."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"753","DOI":"10.1088\/0967-3334\/26\/5\/014","article-title":"Quantitative analysis of contraction patterns in electrical activity signal of pregnant uterus as an alternative to mechanical approach","volume":"26","author":"Jezewski","year":"2005","journal-title":"Physiol. Meas."},{"key":"ref_24","unstructured":"Chendeb, M. (2006). D\u00e9tection et Classification des Signaux non Stationnaires par Utilisation des Ondelettes. Application aux Signaux \u00c9lectromyographiques Ut\u00e9rins. [Ph.D. Thesis, Universit\u00e9 de Technologie de Troyes]."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12884-018-1778-1","article-title":"Automated electrohysterographic detection of uterine contractions for monitoring of pregnancy: Feasibility and prospects","volume":"18","author":"Muszynski","year":"2018","journal-title":"BMC Pregnancy Childbirth"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Rooijakkers, M.J., Song, S., Rabotti, C., Oei, S.G., Bergmans, J.W., Cantatore, E., and Mischi, M. (2014). Influence of electrode placement on signal quality for ambulatory pregnancy monitoring. Comput. Math. Methods Med., 2014.","DOI":"10.1155\/2014\/960980"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1088\/0967-3334\/30\/10\/006","article-title":"Magnetomyographic recording and identification of uterine contractions using Hilbert-wavelet transforms","volume":"30","author":"Furdea","year":"2009","journal-title":"Physiol. Meas."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Peng, J., Hao, D., Liu, H., Liu, J., Zhou, X., and Zheng, D. (2019). Preliminary Study on the Efficient Electrohysterogram Segments for Recognizing Uterine Contractions with Convolutional Neural Networks. Biomed Res. Int., 2019.","DOI":"10.1155\/2019\/3168541"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Liu, Z., Hao, D., Zhang, L., Liu, J., Zhou, X., Yang, L., Yang, Y., Li, X., Zhang, S., and Zheng, D. (2017, January 11\u201315). Comparison of electrohysterogram characteristics during uterine contraction and non-contraction during labor. Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Jeju Island, Korea.","DOI":"10.1109\/EMBC.2017.8037469"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"103897","DOI":"10.1016\/j.compbiomed.2020.103897","article-title":"Uterine contractions clustering based on electrohysterography","volume":"123","author":"Esgalhado","year":"2020","journal-title":"Comput. Biol. Med."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/sdata.2015.17","article-title":"The Icelandic 16-electrode electrohysterogram database","volume":"2","author":"Alexandersson","year":"2015","journal-title":"Sci. Data"},{"key":"ref_32","unstructured":"Sousa, C. (2015). Electrohysterogram Signal Component Cataloging with Spectral and Time-Frequency Methods. [Master\u2019s Thesis, Universidade Nova de Lisboa]."},{"key":"ref_33","unstructured":"Esgalhado, F. (2018). Uterine Contractions Clustering Based on Surface Electromyography: An Input for Pregnancy Monitoring. [Master\u2019s Thesis, Lisbon University]."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.compbiomed.2016.07.003","article-title":"A multichannel time\u2013frequency and multi-wavelet toolbox for uterine electromyography processing and visualisation","volume":"76","author":"Batista","year":"2016","journal-title":"Comput. Biol. Med."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Rooijakkers, M.J., Rabotti, C., Oei, S.G., Aarts, R.M., and Mischi, M. (2013, January 3\u20137). Low-complexity intrauterine pressure monitoring by Teager energy estimation. Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan.","DOI":"10.1109\/EMBC.2013.6611274"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1088\/0967-3334\/29\/7\/011","article-title":"Estimation of internal uterine pressure by joint amplitude and frequency analysis of electrohysterographic signals","volume":"29","author":"Rabotti","year":"2008","journal-title":"Physiol. Meas."},{"key":"ref_37","unstructured":"Kaiser, J.F. (1990, January 3\u20136). On a Simple Algorithm to Calculate the \u2018energy\u2019 of a Signal. Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, Albuquerque, NM, USA."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Chen, L., and Hao, Y. (2017). Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine. Comput. Math. Methods Med., 2017.","DOI":"10.1155\/2017\/7949507"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Jager, F., Liben\u0161ek, S., and Ger\u0161ak, K. (2018). Characterization and Automatic Classification of Preterm and Term Uterine records. PLoS ONE, 13.","DOI":"10.1101\/349266"},{"key":"ref_40","unstructured":"Hassan, M. (2015). Analysis of the Propagation of Uterine Electrical Activity Applied To Predict Preterm Labor. [Ph.D. Thesis, Universit\u00e9 de Technologie de Compi\u00e8gne]."}],"container-title":["Applied Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-3417\/10\/20\/7014\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:17:52Z","timestamp":1760177872000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-3417\/10\/20\/7014"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,9]]},"references-count":40,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2020,10]]}},"alternative-id":["app10207014"],"URL":"https:\/\/doi.org\/10.3390\/app10207014","relation":{},"ISSN":["2076-3417"],"issn-type":[{"value":"2076-3417","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,9]]}}}