Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram

Detalhes bibliográficos
Autor(a) principal: Martins, Daniela
Data de Publicação: 2022
Outros Autores: Batista, Arnaldo, Mouriño, Helena, Russo, Sara, Esgalhado, Filipa, dos Reis, Catarina R. Palma, Serrano, Fátima, Ortigueira, Manuel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/146334
Resumo: Publisher Copyright: © 2022 by the authors.
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spelling Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogramadaptive filtersalvarez waveselectrohystherographypregnancy monitoringrespiratory electromyographyuterine electromyographyAnalytical ChemistryInformation SystemsBiochemistryAtomic and Molecular Physics, and OpticsInstrumentationElectrical and Electronic EngineeringPublisher Copyright: © 2022 by the authors.The electrohysterogram (EHG) is the uterine muscle electromyogram recorded at the abdominal surface of pregnant or non-pregnant woman. The maternal respiration electromyographic signal (MR-EMG) is one of the most relevant interferences present in an EHG. Alvarez (Alv) waves are components of the EHG that have been indicated as having the potential for preterm and term birth prediction. The MR-EMG component in the EHG represents an issue, regarding Alv wave application for pregnancy monitoring, for instance, in preterm birth prediction, a subject of great research interest. Therefore, the Alv waves denoising method should be designed to include the interference MR-EMG attenuation, without compromising the original waves. Adaptive filter properties make them suitable for this task. However, selecting the optimal adaptive filter and its parameters is an important task for the success of the filtering operation. In this work, an algorithm is presented for the automatic adaptive filter and parameter selection using synthetic data. The filter selection pool comprised sixteen candidates, from which, the Wiener, recursive least squares (RLS), householder recursive least squares (HRLS), and QR-decomposition recursive least squares (QRD-RLS) were the best performers. The optimized parameters were L = 2 (filter length) for all of them and λ = 1 (forgetting factor) for the last three. The developed optimization algorithm may be of interest to other applications. The optimized filters were applied to real data. The result was the attenuation of the MR-EMG in Alv waves power. For the Wiener filter, power reductions for quartile 1, median, and quartile 3 were found to be −16.74%, −20.32%, and −15.78%, respectively (p-value = 1.31 × 10−12).DF – Departamento de FísicaUNINOVA-Instituto de Desenvolvimento de Novas TecnologiasCTS - Centro de Tecnologia e SistemasNOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)RUNMartins, DanielaBatista, ArnaldoMouriño, HelenaRusso, SaraEsgalhado, Filipados Reis, Catarina R. PalmaSerrano, FátimaOrtigueira, Manuel2022-12-16T22:16:24Z2022-102022-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article26application/pdfhttp://hdl.handle.net/10362/146334eng1424-8220PURE: 47332574https://doi.org/10.3390/s22197638info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:27:25Zoai:run.unl.pt:10362/146334Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:52:35.879687Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram
title Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram
spellingShingle Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram
Martins, Daniela
adaptive filters
alvarez waves
electrohystherography
pregnancy monitoring
respiratory electromyography
uterine electromyography
Analytical Chemistry
Information Systems
Biochemistry
Atomic and Molecular Physics, and Optics
Instrumentation
Electrical and Electronic Engineering
title_short Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram
title_full Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram
title_fullStr Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram
title_full_unstemmed Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram
title_sort Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram
author Martins, Daniela
author_facet Martins, Daniela
Batista, Arnaldo
Mouriño, Helena
Russo, Sara
Esgalhado, Filipa
dos Reis, Catarina R. Palma
Serrano, Fátima
Ortigueira, Manuel
author_role author
author2 Batista, Arnaldo
Mouriño, Helena
Russo, Sara
Esgalhado, Filipa
dos Reis, Catarina R. Palma
Serrano, Fátima
Ortigueira, Manuel
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv DF – Departamento de Física
UNINOVA-Instituto de Desenvolvimento de Novas Tecnologias
CTS - Centro de Tecnologia e Sistemas
NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
RUN
dc.contributor.author.fl_str_mv Martins, Daniela
Batista, Arnaldo
Mouriño, Helena
Russo, Sara
Esgalhado, Filipa
dos Reis, Catarina R. Palma
Serrano, Fátima
Ortigueira, Manuel
dc.subject.por.fl_str_mv adaptive filters
alvarez waves
electrohystherography
pregnancy monitoring
respiratory electromyography
uterine electromyography
Analytical Chemistry
Information Systems
Biochemistry
Atomic and Molecular Physics, and Optics
Instrumentation
Electrical and Electronic Engineering
topic adaptive filters
alvarez waves
electrohystherography
pregnancy monitoring
respiratory electromyography
uterine electromyography
Analytical Chemistry
Information Systems
Biochemistry
Atomic and Molecular Physics, and Optics
Instrumentation
Electrical and Electronic Engineering
description Publisher Copyright: © 2022 by the authors.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-16T22:16:24Z
2022-10
2022-10-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/146334
url http://hdl.handle.net/10362/146334
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1424-8220
PURE: 47332574
https://doi.org/10.3390/s22197638
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 26
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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