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Titre : Developpement de techniques utilisant les ondelettes pour l’analyse, : La classification et le traitement du signal ECG Type de document : texte imprimé Auteurs : Skander Bensegueni, Auteur ; Abdelhak Bennia, Directeur de thèse Editeur : جامعة الإخوة منتوري قسنطينة Année de publication : 2016 Importance : 104 f. Format : 30 cm. Note générale : 2 copies imprimées disponibles
Langues : Français (fre) Catégories : Français - Anglais
ElectroniqueTags : signal électrocardiogramme pic R détection d'ondes compression du signal transformée en ondelettes analyse en composantes principale transformée en cosinus discrète ECG signal R peak waves detection signal compression wavelets transform principal components analysis discrete cosine transform ??????? ???????? ?????????? ????? ?????? ?? ????? ?? ?????? ????? ??? ??????? ????? ???????? ????? ???????? ???????? ????? ??? ?????? ??? ???????? Index. décimale : 621 Electronique Résumé : n this thesis, we tried to address several topics concerning the analysis, synthesis and compression of the electrocardiogram (ECG) signal using the MIT database. Where we have detected R waves by locating each QRS complex using the dyadic wavelet transform, which defines a window of R peak search, and then, we have accurately detected the R waves by the manipulation of the first order coefficients of the discrete wavelet transform. In the second part of our work we have segmented the signal in its RR periods in order to construct vectors of a data matrix, where we extract its principal components in order to reduce the size of the information, then, we reduce more and more the size by applying a threshold on the signal resulting from the discrete cosine transform. The last algorithm designed is a practical application of the R wave detection algorithm, but, after the extraction of one-dimensional signal of the resulting scanned image of the ECG paper.
The results of R peaks detection, reducing the size of the signal and the correspondence of samples of the signal resulting from the extraction with those of the original file, was very satisfactory and with an extreme precision,
demonstrating the quality of our algorithms presented in this thesis.Diplôme : Doctorat en sciences En ligne : ../theses/electronique/BEN6877.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=10193 Developpement de techniques utilisant les ondelettes pour l’analyse, : La classification et le traitement du signal ECG [texte imprimé] / Skander Bensegueni, Auteur ; Abdelhak Bennia, Directeur de thèse . - [S.l.] : جامعة الإخوة منتوري قسنطينة, 2016 . - 104 f. ; 30 cm.
2 copies imprimées disponibles
Langues : Français (fre)
Catégories : Français - Anglais
ElectroniqueTags : signal électrocardiogramme pic R détection d'ondes compression du signal transformée en ondelettes analyse en composantes principale transformée en cosinus discrète ECG signal R peak waves detection signal compression wavelets transform principal components analysis discrete cosine transform ??????? ???????? ?????????? ????? ?????? ?? ????? ?? ?????? ????? ??? ??????? ????? ???????? ????? ???????? ???????? ????? ??? ?????? ??? ???????? Index. décimale : 621 Electronique Résumé : n this thesis, we tried to address several topics concerning the analysis, synthesis and compression of the electrocardiogram (ECG) signal using the MIT database. Where we have detected R waves by locating each QRS complex using the dyadic wavelet transform, which defines a window of R peak search, and then, we have accurately detected the R waves by the manipulation of the first order coefficients of the discrete wavelet transform. In the second part of our work we have segmented the signal in its RR periods in order to construct vectors of a data matrix, where we extract its principal components in order to reduce the size of the information, then, we reduce more and more the size by applying a threshold on the signal resulting from the discrete cosine transform. The last algorithm designed is a practical application of the R wave detection algorithm, but, after the extraction of one-dimensional signal of the resulting scanned image of the ECG paper.
The results of R peaks detection, reducing the size of the signal and the correspondence of samples of the signal resulting from the extraction with those of the original file, was very satisfactory and with an extreme precision,
demonstrating the quality of our algorithms presented in this thesis.Diplôme : Doctorat en sciences En ligne : ../theses/electronique/BEN6877.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=10193 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité BEN/6877 BEN/6877 Thèse Bibliothèque principale Thèses Disponible Analyse et classification des maladies cardiaques et respiratoires en utilisant les operateurs et les systemes d’ordre fractionnaire. / Imene Assadi ép Bensouici
Titre : Analyse et classification des maladies cardiaques et respiratoires en utilisant les operateurs et les systemes d’ordre fractionnaire. Type de document : texte imprimé Auteurs : Imene Assadi ép Bensouici, Auteur ; Abdelfatah Charef, Directeur de thèse Editeur : جامعة الإخوة منتوري قسنطينة Année de publication : 2018 Importance : 136 f. Format : 30 cm. Note générale : 2 copies imprimées disponibles. Langues : Français (fre) Catégories : Français - Anglais
ElectroniqueTags : Appareil FOT Arythmies cardiaques Classification Complexe QRS Impédance
respiratoire Maladies respiratoires Modélisation Signal ECG Système d'ordre fractionnaire Cardiac Arrhythmias ECG signal FOT device Fractional order system Modeling QRS Complex Respiratory diseases Respiratory impedance ????? ????? ????? ECG ????? ?????? ??????? ????? ????? ??????? ???? FOT ????
??? ???? ????? ?????? QRS ?????? ??????Index. décimale : 621 Electronique Résumé : The work realized in this thesis presents processing and analysis techniques of the electrocardiographic signal (ECG) as well as the respiratory signal for the classification and discrimination of cardiac and respiratory diseases based on fractional order operators and systems. First, the frequency content of the complex QRS of the ECG modeling by a fractional order linear system was presented. After that, classification and discrimination
methods of cardiac arrhythmias have been developed using the proposed complex QRS frequency content fractional order model’s parameters as pertinent parameters. A particular attention is paid to normal beats, premature ectopic (PVC) and right and left branch blocks (RBBB and LBBB). Some classification experiments have been presented using the MIT / BIH database. Then, the respiratory impedance modeling and the respiratory diseases
classification using fractional order operators and systems have been also presented. The respiratory impedance model parameters have been used by a classification algorithm for the healthy subjects, asthmatic and chronic obstructive pulmonary disease (COPD) patient’s discrimination. The classification method was validated using data collected by the forced oscillation technique (FOT) at Ghent University Hospital, Belgium. The obtained results for the frequency content of the QRS and the respiratory impedance modeling and the cardiac and
respiratory diseases discrimination were very satisfactory.
Diplôme : Doctorat En ligne : ../theses/electronique/ASS7200.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=10763 Analyse et classification des maladies cardiaques et respiratoires en utilisant les operateurs et les systemes d’ordre fractionnaire. [texte imprimé] / Imene Assadi ép Bensouici, Auteur ; Abdelfatah Charef, Directeur de thèse . - [S.l.] : جامعة الإخوة منتوري قسنطينة, 2018 . - 136 f. ; 30 cm.
2 copies imprimées disponibles.
Langues : Français (fre)
Catégories : Français - Anglais
ElectroniqueTags : Appareil FOT Arythmies cardiaques Classification Complexe QRS Impédance
respiratoire Maladies respiratoires Modélisation Signal ECG Système d'ordre fractionnaire Cardiac Arrhythmias ECG signal FOT device Fractional order system Modeling QRS Complex Respiratory diseases Respiratory impedance ????? ????? ????? ECG ????? ?????? ??????? ????? ????? ??????? ???? FOT ????
??? ???? ????? ?????? QRS ?????? ??????Index. décimale : 621 Electronique Résumé : The work realized in this thesis presents processing and analysis techniques of the electrocardiographic signal (ECG) as well as the respiratory signal for the classification and discrimination of cardiac and respiratory diseases based on fractional order operators and systems. First, the frequency content of the complex QRS of the ECG modeling by a fractional order linear system was presented. After that, classification and discrimination
methods of cardiac arrhythmias have been developed using the proposed complex QRS frequency content fractional order model’s parameters as pertinent parameters. A particular attention is paid to normal beats, premature ectopic (PVC) and right and left branch blocks (RBBB and LBBB). Some classification experiments have been presented using the MIT / BIH database. Then, the respiratory impedance modeling and the respiratory diseases
classification using fractional order operators and systems have been also presented. The respiratory impedance model parameters have been used by a classification algorithm for the healthy subjects, asthmatic and chronic obstructive pulmonary disease (COPD) patient’s discrimination. The classification method was validated using data collected by the forced oscillation technique (FOT) at Ghent University Hospital, Belgium. The obtained results for the frequency content of the QRS and the respiratory impedance modeling and the cardiac and
respiratory diseases discrimination were very satisfactory.
Diplôme : Doctorat En ligne : ../theses/electronique/ASS7200.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=10763 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité ASS/7200 ASS/7200 Thèse Bibliothèque principale Thèses Disponible
