Serveur sur les données et bibliothèques médicales au Maghreb (version finale)

Attention, ce site est en cours de développement !
Attention, site généré par des moyens informatiques à partir de corpus bruts.
Les informations ne sont donc pas validées.

Noise and baseline wandering suppression of ECG signals by morphological filter.

Identifieur interne : 000723 ( PubMed/Corpus ); précédent : 000722; suivant : 000724

Noise and baseline wandering suppression of ECG signals by morphological filter.

Auteurs : S A Taouli ; F. Bereksi-Reguig

Source :

RBID : pubmed:20028196

English descriptors

Abstract

Electrocardiogram (ECG) signals describe the electrical activity of the heart, and are universally by physicists in the diagnosis of cardiac pathologies. However, during the acquisition of ECGs they are often contaminated with different sources of noise, making interpretation difficult. Different techniques have been used to filter the ECG signal, in order to optimize the signal to noise ratio (S/N). In this paper, an approach based on morphological filtering is developed in order to filter the ECG. Morphological filtering is concerned with the detection of the ECG morphology, therefore allowing the suppression of noises and particularly baseline wandering. The implemented filter is evaluated using signals taken from the MIT-BIH ECG universal database. The results show that the performance of this filter is good compared with other filtering techniques.

DOI: 10.3109/03091900903336886
PubMed: 20028196

Links to Exploration step

pubmed:20028196

Le document en format XML

<record>
<TEI>
<teiHeader>
<fileDesc>
<titleStmt>
<title xml:lang="en">Noise and baseline wandering suppression of ECG signals by morphological filter.</title>
<author>
<name sortKey="Taouli, S A" sort="Taouli, S A" uniqKey="Taouli S" first="S A" last="Taouli">S A Taouli</name>
<affiliation>
<nlm:affiliation>Biomedical Engineering Research Laboratory, Biomedical Electronics Department, Science Engineering Faculty, University Aboubekr Belkaid, BP 230, Tlemcen 13000, Algeria. s_taouli@mail.univ-Tlemcen.dz</nlm:affiliation>
</affiliation>
</author>
<author>
<name sortKey="Bereksi Reguig, F" sort="Bereksi Reguig, F" uniqKey="Bereksi Reguig F" first="F" last="Bereksi-Reguig">F. Bereksi-Reguig</name>
</author>
</titleStmt>
<publicationStmt>
<idno type="wicri:source">PubMed</idno>
<date when="2010">2010</date>
<idno type="RBID">pubmed:20028196</idno>
<idno type="pmid">20028196</idno>
<idno type="doi">10.3109/03091900903336886</idno>
<idno type="wicri:Area/PubMed/Corpus">000723</idno>
<idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000723</idno>
</publicationStmt>
<sourceDesc>
<biblStruct>
<analytic>
<title xml:lang="en">Noise and baseline wandering suppression of ECG signals by morphological filter.</title>
<author>
<name sortKey="Taouli, S A" sort="Taouli, S A" uniqKey="Taouli S" first="S A" last="Taouli">S A Taouli</name>
<affiliation>
<nlm:affiliation>Biomedical Engineering Research Laboratory, Biomedical Electronics Department, Science Engineering Faculty, University Aboubekr Belkaid, BP 230, Tlemcen 13000, Algeria. s_taouli@mail.univ-Tlemcen.dz</nlm:affiliation>
</affiliation>
</author>
<author>
<name sortKey="Bereksi Reguig, F" sort="Bereksi Reguig, F" uniqKey="Bereksi Reguig F" first="F" last="Bereksi-Reguig">F. Bereksi-Reguig</name>
</author>
</analytic>
<series>
<title level="j">Journal of medical engineering & technology</title>
<idno type="eISSN">1464-522X</idno>
<imprint>
<date when="2010" type="published">2010</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc>
<textClass>
<keywords scheme="KwdEn" xml:lang="en">
<term>Algorithms (MeSH)</term>
<term>Electrocardiography (methods)</term>
<term>Humans (MeSH)</term>
<term>Models, Theoretical (MeSH)</term>
<term>Signal Processing, Computer-Assisted (MeSH)</term>
</keywords>
<keywords scheme="MESH" qualifier="methods" xml:lang="en">
<term>Electrocardiography</term>
</keywords>
<keywords scheme="MESH" xml:lang="en">
<term>Algorithms</term>
<term>Humans</term>
<term>Models, Theoretical</term>
<term>Signal Processing, Computer-Assisted</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">Electrocardiogram (ECG) signals describe the electrical activity of the heart, and are universally by physicists in the diagnosis of cardiac pathologies. However, during the acquisition of ECGs they are often contaminated with different sources of noise, making interpretation difficult. Different techniques have been used to filter the ECG signal, in order to optimize the signal to noise ratio (S/N). In this paper, an approach based on morphological filtering is developed in order to filter the ECG. Morphological filtering is concerned with the detection of the ECG morphology, therefore allowing the suppression of noises and particularly baseline wandering. The implemented filter is evaluated using signals taken from the MIT-BIH ECG universal database. The results show that the performance of this filter is good compared with other filtering techniques.</div>
</front>
</TEI>
<pubmed>
<MedlineCitation Status="MEDLINE" Owner="NLM">
<PMID Version="1">20028196</PMID>
<DateCompleted>
<Year>2010</Year>
<Month>03</Month>
<Day>26</Day>
</DateCompleted>
<DateRevised>
<Year>2011</Year>
<Month>05</Month>
<Day>25</Day>
</DateRevised>
<Article PubModel="Print">
<Journal>
<ISSN IssnType="Electronic">1464-522X</ISSN>
<JournalIssue CitedMedium="Internet">
<Volume>34</Volume>
<Issue>2</Issue>
<PubDate>
<Year>2010</Year>
<Month>Feb</Month>
</PubDate>
</JournalIssue>
<Title>Journal of medical engineering & technology</Title>
<ISOAbbreviation>J Med Eng Technol</ISOAbbreviation>
</Journal>
<ArticleTitle>Noise and baseline wandering suppression of ECG signals by morphological filter.</ArticleTitle>
<Pagination>
<MedlinePgn>87-96</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.3109/03091900903336886</ELocationID>
<Abstract>
<AbstractText>Electrocardiogram (ECG) signals describe the electrical activity of the heart, and are universally by physicists in the diagnosis of cardiac pathologies. However, during the acquisition of ECGs they are often contaminated with different sources of noise, making interpretation difficult. Different techniques have been used to filter the ECG signal, in order to optimize the signal to noise ratio (S/N). In this paper, an approach based on morphological filtering is developed in order to filter the ECG. Morphological filtering is concerned with the detection of the ECG morphology, therefore allowing the suppression of noises and particularly baseline wandering. The implemented filter is evaluated using signals taken from the MIT-BIH ECG universal database. The results show that the performance of this filter is good compared with other filtering techniques.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y">
<Author ValidYN="Y">
<LastName>Taouli</LastName>
<ForeName>S A</ForeName>
<Initials>SA</Initials>
<AffiliationInfo>
<Affiliation>Biomedical Engineering Research Laboratory, Biomedical Electronics Department, Science Engineering Faculty, University Aboubekr Belkaid, BP 230, Tlemcen 13000, Algeria. s_taouli@mail.univ-Tlemcen.dz</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Bereksi-Reguig</LastName>
<ForeName>F</ForeName>
<Initials>F</Initials>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList>
<PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D016454">Review</PublicationType>
</PublicationTypeList>
</Article>
<MedlineJournalInfo>
<Country>England</Country>
<MedlineTA>J Med Eng Technol</MedlineTA>
<NlmUniqueID>7702125</NlmUniqueID>
<ISSNLinking>0309-1902</ISSNLinking>
</MedlineJournalInfo>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList>
<MeshHeading>
<DescriptorName UI="D000465" MajorTopicYN="N">Algorithms</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D004562" MajorTopicYN="N">Electrocardiography</DescriptorName>
<QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D008962" MajorTopicYN="N">Models, Theoretical</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D012815" MajorTopicYN="Y">Signal Processing, Computer-Assisted</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<NumberOfReferences>26</NumberOfReferences>
</MedlineCitation>
<PubmedData>
<History>
<PubMedPubDate PubStatus="entrez">
<Year>2009</Year>
<Month>12</Month>
<Day>24</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed">
<Year>2009</Year>
<Month>12</Month>
<Day>24</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline">
<Year>2010</Year>
<Month>3</Month>
<Day>27</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList>
<ArticleId IdType="pubmed">20028196</ArticleId>
<ArticleId IdType="doi">10.3109/03091900903336886</ArticleId>
</ArticleIdList>
</PubmedData>
</pubmed>
</record>

Pour manipuler ce document sous Unix (Dilib)

EXPLOR_STEP=$WICRI_ROOT/Wicri/Sante/explor/MaghrebDataLibMedV2/Data/PubMed/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000723 | SxmlIndent | more

Ou

HfdSelect -h $EXPLOR_AREA/Data/PubMed/Corpus/biblio.hfd -nk 000723 | SxmlIndent | more

Pour mettre un lien sur cette page dans le réseau Wicri

{{Explor lien
   |wiki=    Wicri/Sante
   |area=    MaghrebDataLibMedV2
   |flux=    PubMed
   |étape=   Corpus
   |type=    RBID
   |clé=     pubmed:20028196
   |texte=   Noise and baseline wandering suppression of ECG signals by morphological filter.
}}

Pour générer des pages wiki

HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Corpus/RBID.i   -Sk "pubmed:20028196" \
       | HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Corpus/biblio.hfd   \
       | NlmPubMed2Wicri -a MaghrebDataLibMedV2 

Wicri

This area was generated with Dilib version V0.6.38.
Data generation: Wed Jun 30 18:27:05 2021. Site generation: Wed Jun 30 18:34:21 2021