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Recurrence quantification analysis of uterine vectormyometriogram to identify pregnant women with threatened preterm labor

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Recurrence quantification analysis of uterine vectormyometriogram to identify pregnant women with threatened preterm labor

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dc.contributor.author Nieto del-Amor, Félix es_ES
dc.contributor.author Prats-Boluda, Gema es_ES
dc.contributor.author Li, Wanting es_ES
dc.contributor.author Martínez-de-Juan, José L. es_ES
dc.contributor.author Yang, Lin es_ES
dc.contributor.author Yang, Yongxiu es_ES
dc.contributor.author Hao, Dongmei es_ES
dc.contributor.author Ye Lin, Yiyao es_ES
dc.date.accessioned 2024-06-06T18:16:17Z
dc.date.available 2024-06-06T18:16:17Z
dc.date.issued 2024-03 es_ES
dc.identifier.issn 1746-8094 es_ES
dc.identifier.uri http://hdl.handle.net/10251/204776
dc.description.abstract [EN] Electrohysterography has been shown to provide relevant information on preventing preterm labor. Recent studies have confirmed the feasibility of using the vectormyometriogram (VMG) to assess uterine myoelectric vector displacement, with different physiological implications for the slow and fast waves, without suggesting its implementation in clinical practice. The fast wave VMG component has dynamic behavior in any specific direction on the X-Y plane. Since recurrence is a common feature of dynamic systems, we aimed to determine the recurrence pattern of uterine vector displacement, exploring its clinical potential in detecting imminent and preterm labor in women with threatened preterm labor and a serious preterm birth risk. For this, we analyzed the recurrence patterns from a 2D-vectormyometriogram using four common statistics: determinism, longest diagonal, entropy, and laminarity. We found significantly increased determinism (0.035 ± 0.011 vs. 0.077 ± 0.041), entropy (1.768 ± 0.116 vs. 2.197 ± 0.24) and laminarity (0.086 ± 0.034 vs. 0.173 ± 0.078) from the early (26¿30 weeks) to late (35¿37 weeks) gestation stages. As pregnancy progresses, the uterine vector displacement becomes more periodic, predictable and stable, while VMG recurrence statistics in the fast wave high bandwidth better detect imminent and preterm labor, outperforming classical EHG parameters from bipolar channels. The proposed method was also resistant to motion artifacts and preserved its discriminative capacity between the groups. Our results on VMG recurrence statistics could thus be another reliable biomarker for preventing preterm labor in women with threatened preterm labor and would favor transferring the EHG technique to clinical practice. es_ES
dc.description.sponsorship This work was supported by the Spanish Ministry of Science and Innovation and the European Regional Development Fund, State Plan for Scientific, Technical and Innovation Research 2021 - 2023 (PID2021-124038OB-I00) . 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. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Biomedical Signal Processing and Control es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Preterm labor es_ES
dc.subject Vectormyometriogram es_ES
dc.subject RQA es_ES
dc.subject Recurrence plot es_ES
dc.subject Electrohysterography es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Recurrence quantification analysis of uterine vectormyometriogram to identify pregnant women with threatened preterm labor es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.bspc.2023.105795 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//PID2021-124038OB-I00//INTELIGENCIA ARTIFICIAL PARA LA AYUDA AL DIAGNÓSTICO EN TIEMPO REAL DEL PARTO PREMATURO BASADO EN LA ACTIVIDAD MIOELÉCTRICA UTERINA. ÉNFASIS EN GESTACIONES MÚLTIPLES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSFC//U20A20388/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NKRDPC//2019YFC0119700/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation Nieto Del-Amor, F.; Prats-Boluda, G.; Li, W.; Martínez-De-Juan, JL.; Yang, L.; Yang, Y.; Hao, D.... (2024). Recurrence quantification analysis of uterine vectormyometriogram to identify pregnant women with threatened preterm labor. Biomedical Signal Processing and Control. 89. https://doi.org/10.1016/j.bspc.2023.105795 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.bspc.2023.105795 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 89 es_ES
dc.relation.pasarela S\505938 es_ES
dc.contributor.funder AGENCIA ESTATAL DE INVESTIGACION es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
dc.contributor.funder National Natural Science Foundation of China es_ES
dc.contributor.funder National Key Research and Development Program of China es_ES
dc.subject.ods 03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades es_ES
dc.subject.ods 05.- Alcanzar la igualdad entre los géneros y empoderar a todas las mujeres y niñas es_ES
dc.subject.ods 10.- Reducir las desigualdades entre países y dentro de ellos es_ES


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