PVC discrimination using the QRS power spectrum and self-organizing maps.
Identifieur interne : 000070 ( Main/Exploration ); précédent : 000069; suivant : 000071PVC discrimination using the QRS power spectrum and self-organizing maps.
Auteurs : M L Talbi [Algérie] ; A. CharefSource :
- Computer methods and programs in biomedicine [ 1872-7565 ] ; 2009.
Descripteurs français
- KwdFr :
- Algorithmes (MeSH), Automatisation (méthodes), Biologie informatique (méthodes), Cardiologie (instrumentation), Cardiologie (méthodes), Extrasystoles ventriculaires (diagnostic), Extrasystoles ventriculaires (physiopathologie), Humains (MeSH), Intelligence artificielle (MeSH), Modèles statistiques (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), Troubles du rythme cardiaque (physiopathologie), Électrocardiographie (méthodes).
- MESH :
- diagnostic : Extrasystoles ventriculaires, Troubles du rythme cardiaque.
- méthodes : Automatisation, Biologie informatique, Cardiologie, Reconnaissance automatique des formes, Électrocardiographie.
- physiopathologie : Extrasystoles ventriculaires, Troubles du rythme cardiaque.
- instrumentation : Algorithmes, Cardiologie, Humains, Intelligence artificielle, Modèles statistiques, Reproductibilité des résultats, Sensibilité et spécificité, Traitement du signal assisté par ordinateur.
English descriptors
- KwdEn :
- Algorithms (MeSH), Arrhythmias, Cardiac (diagnosis), Arrhythmias, Cardiac (physiopathology), Artificial Intelligence (MeSH), Automation (methods), Cardiology (instrumentation), Cardiology (methods), Computational Biology (methods), Electrocardiography (methods), Humans (MeSH), Models, Statistical (MeSH), Pattern Recognition, Automated (methods), Reproducibility of Results (MeSH), Sensitivity and Specificity (MeSH), Signal Processing, Computer-Assisted (MeSH), Ventricular Premature Complexes (diagnosis), Ventricular Premature Complexes (physiopathology).
- MESH :
- diagnosis : Arrhythmias, Cardiac, Ventricular Premature Complexes.
- instrumentation : Cardiology.
- methods : Automation, Cardiology, Computational Biology, Electrocardiography, Pattern Recognition, Automated.
- physiopathology : Arrhythmias, Cardiac, Ventricular Premature Complexes.
- Algorithms, Artificial Intelligence, Humans, Models, Statistical, Reproducibility of Results, Sensitivity and Specificity, Signal Processing, Computer-Assisted.
Abstract
This paper deals with the discrimination of premature ventricular contraction (PVC) arrhythmia using the fractal behavior of the power spectrum density of the QRS complexes. The linear interpolation of the QRS complex power spectrum density in Bode diagram in two different frequency intervals gives two straight lines with two different slopes. The scatter plot of one slope versus the other shows that there exists two distinct regions which represent the normal beats and the PVC beats. Therefore the PVC beats are classified using a self-organizing map fed by the two slopes of the QRS complex power spectrum. The MIT/BIH arrhythmia database is then used to evaluate the usefulness of the proposed method in the discrimination of the premature ventricular contraction (PVC) arrhythmia. The results have indicated that the method has achieved 82.71% of sensitivity and 88.06% of specificity over 46 records from the MIT-BIH arrhythmia database.
DOI: 10.1016/j.cmpb.2008.12.009
PubMed: 19215994
Affiliations:
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Le document en format XML
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms (MeSH)</term>
<term>Arrhythmias, Cardiac (diagnosis)</term>
<term>Arrhythmias, Cardiac (physiopathology)</term>
<term>Artificial Intelligence (MeSH)</term>
<term>Automation (methods)</term>
<term>Cardiology (instrumentation)</term>
<term>Cardiology (methods)</term>
<term>Computational Biology (methods)</term>
<term>Electrocardiography (methods)</term>
<term>Humans (MeSH)</term>
<term>Models, Statistical (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>
<term>Ventricular Premature Complexes (diagnosis)</term>
<term>Ventricular Premature Complexes (physiopathology)</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes (MeSH)</term>
<term>Automatisation (méthodes)</term>
<term>Biologie informatique (méthodes)</term>
<term>Cardiologie (instrumentation)</term>
<term>Cardiologie (méthodes)</term>
<term>Extrasystoles ventriculaires (diagnostic)</term>
<term>Extrasystoles ventriculaires (physiopathologie)</term>
<term>Humains (MeSH)</term>
<term>Intelligence artificielle (MeSH)</term>
<term>Modèles statistiques (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>Troubles du rythme cardiaque (physiopathologie)</term>
<term>Électrocardiographie (méthodes)</term>
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<keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Arrhythmias, Cardiac</term>
<term>Ventricular Premature Complexes</term>
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<term>Troubles du rythme cardiaque</term>
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<keywords scheme="MESH" qualifier="instrumentation" xml:lang="en"><term>Cardiology</term>
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<keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Automation</term>
<term>Cardiology</term>
<term>Computational Biology</term>
<term>Electrocardiography</term>
<term>Pattern Recognition, Automated</term>
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<term>Biologie informatique</term>
<term>Cardiologie</term>
<term>Reconnaissance automatique des formes</term>
<term>Électrocardiographie</term>
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<term>Troubles du rythme cardiaque</term>
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<keywords scheme="MESH" qualifier="physiopathology" xml:lang="en"><term>Arrhythmias, Cardiac</term>
<term>Ventricular Premature Complexes</term>
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<keywords scheme="MESH" xml:lang="en"><term>Algorithms</term>
<term>Artificial Intelligence</term>
<term>Humans</term>
<term>Models, Statistical</term>
<term>Reproducibility of Results</term>
<term>Sensitivity and Specificity</term>
<term>Signal Processing, Computer-Assisted</term>
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<keywords scheme="MESH" qualifier="instrumentation" xml:lang="fr"><term>Algorithmes</term>
<term>Cardiologie</term>
<term>Humains</term>
<term>Intelligence artificielle</term>
<term>Modèles statistiques</term>
<term>Reproductibilité des résultats</term>
<term>Sensibilité et spécificité</term>
<term>Traitement du signal assisté par ordinateur</term>
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<front><div type="abstract" xml:lang="en">This paper deals with the discrimination of premature ventricular contraction (PVC) arrhythmia using the fractal behavior of the power spectrum density of the QRS complexes. The linear interpolation of the QRS complex power spectrum density in Bode diagram in two different frequency intervals gives two straight lines with two different slopes. The scatter plot of one slope versus the other shows that there exists two distinct regions which represent the normal beats and the PVC beats. Therefore the PVC beats are classified using a self-organizing map fed by the two slopes of the QRS complex power spectrum. The MIT/BIH arrhythmia database is then used to evaluate the usefulness of the proposed method in the discrimination of the premature ventricular contraction (PVC) arrhythmia. The results have indicated that the method has achieved 82.71% of sensitivity and 88.06% of specificity over 46 records from the MIT-BIH arrhythmia database.</div>
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