Fractional wavelet for R-Wave detection in ECG signal.
Identifieur interne : 000089 ( Main/Exploration ); précédent : 000088; suivant : 000090Fractional wavelet for R-Wave detection in ECG signal.
Auteurs : A. Charef [Algérie] ; F. AbdellicheSource :
- Critical reviews in biomedical engineering [ 0278-940X ] ; 2008.
Descripteurs français
- KwdFr :
- Algorithmes (MeSH), Diagnostic assisté par ordinateur (méthodes), Humains (MeSH), Reconnaissance automatique des formes (méthodes), Reproductibilité des résultats (MeSH), Sensibilité et spécificité (MeSH), Traitement du signal assisté par ordinateur (MeSH), Troubles du rythme cardiaque (diagnostic), Électrocardiographie (méthodes).
- MESH :
English descriptors
- KwdEn :
- MESH :
Abstract
In this paper, we propose a method for the R-wave detection of the QRS complex of the ECG signal using a fractional wavelet. This fractional wavelet is defined, in this context, as the second derivative of the Cole-Cole distribution function of relaxation times, which is widely used in mathematical modeling of fractional order systems. In order to reduce the noise level for the ECG data, our detection algorithm incorporates the proposed fractional wavelet whose parameters are obtained by maximizing the signal-to-noise ratio of the ECG. The scales of this wavelet are chosen based on the spectral characteristics of the ECG. The proposed algorithm performances were evaluated using the MIT-BIH arrhythmia database. The numerical results show that the proposed algorithm achieved a detection rate of about 99.56%.
DOI: 10.1615/critrevbiomedeng.v36.i2-3.10
PubMed: 19740068
Affiliations:
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Le document en format XML
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Charef</name><affiliation wicri:level="1"><nlm:affiliation>Département d'Electronique, Université Mentouri, Route Ain El Bey, Constantine, Algeria. abdelliche_faycal@yahoo.fr</nlm:affiliation><country xml:lang="fr">Algérie</country><wicri:regionArea>Département d'Electronique, Université Mentouri, Route Ain El Bey, Constantine</wicri:regionArea><wicri:noRegion>Constantine</wicri:noRegion></affiliation></author><author><name sortKey="Abdelliche, F" sort="Abdelliche, F" uniqKey="Abdelliche F" first="F" last="Abdelliche">F. Abdelliche</name></author></analytic><series><title level="j">Critical reviews in biomedical engineering</title><idno type="ISSN">0278-940X</idno><imprint><date when="2008" type="published">2008</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms (MeSH)</term><term>Arrhythmias, Cardiac (diagnosis)</term><term>Diagnosis, Computer-Assisted (methods)</term><term>Electrocardiography (methods)</term><term>Humans (MeSH)</term><term>Pattern Recognition, Automated (methods)</term><term>Reproducibility of Results (MeSH)</term><term>Sensitivity and Specificity (MeSH)</term><term>Signal Processing, Computer-Assisted (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes (MeSH)</term><term>Diagnostic assisté par ordinateur (méthodes)</term><term>Humains (MeSH)</term><term>Reconnaissance automatique des formes (méthodes)</term><term>Reproductibilité des résultats (MeSH)</term><term>Sensibilité et spécificité (MeSH)</term><term>Traitement du signal assisté par ordinateur (MeSH)</term><term>Troubles du rythme cardiaque (diagnostic)</term><term>Électrocardiographie (méthodes)</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Arrhythmias, Cardiac</term></keywords><keywords scheme="MESH" qualifier="diagnostic" xml:lang="fr"><term>Troubles du rythme cardiaque</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Diagnosis, Computer-Assisted</term><term>Electrocardiography</term><term>Pattern Recognition, Automated</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Diagnostic assisté par ordinateur</term><term>Reconnaissance automatique des formes</term><term>Électrocardiographie</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Humans</term><term>Reproducibility of Results</term><term>Sensitivity and Specificity</term><term>Signal Processing, Computer-Assisted</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Humains</term><term>Reproductibilité des résultats</term><term>Sensibilité et spécificité</term><term>Traitement du signal assisté par ordinateur</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In this paper, we propose a method for the R-wave detection of the QRS complex of the ECG signal using a fractional wavelet. This fractional wavelet is defined, in this context, as the second derivative of the Cole-Cole distribution function of relaxation times, which is widely used in mathematical modeling of fractional order systems. In order to reduce the noise level for the ECG data, our detection algorithm incorporates the proposed fractional wavelet whose parameters are obtained by maximizing the signal-to-noise ratio of the ECG. The scales of this wavelet are chosen based on the spectral characteristics of the ECG. The proposed algorithm performances were evaluated using the MIT-BIH arrhythmia database. The numerical results show that the proposed algorithm achieved a detection rate of about 99.56%.</div></front></TEI><affiliations><list><country><li>Algérie</li></country></list><tree><noCountry><name sortKey="Abdelliche, F" sort="Abdelliche, F" uniqKey="Abdelliche F" first="F" last="Abdelliche">F. Abdelliche</name></noCountry><country name="Algérie"><noRegion><name sortKey="Charef, A" sort="Charef, A" uniqKey="Charef A" first="A" last="Charef">A. Charef</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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