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Fouille de dynamiques multivariées, application à des données temporelles en cardiologie.

Abstract : This manuscript focuses on the problem of analysing dynamics of time series observed in cardiology. The proposed solution is divided into two steps. The first one consists in the extraction of useful information from the ECG by segmenting each beat with a wavelet decomposition algorithmn, adapted from the litterature. The difficult problem of optimising both thresholds and time windows is solved with evolutionary algorithms. The second step relies on Hidden Semi-Markovian models to represent the time series made up of the extracted variables. An algorithm of unsupervised classification is proposed to retrieve the natural groups. The application of this method to the detection of ischemic episodes and to the analysis of stress ECG from patients suffering from Brugada syndrome presents a higher performance than more tradionnal approaches.
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https://tel.archives-ouvertes.fr/tel-00364720
Contributor : Jerome Dumont <>
Submitted on : Thursday, February 26, 2009 - 7:35:15 PM
Last modification on : Thursday, January 14, 2021 - 11:24:56 AM
Long-term archiving on: : Friday, October 12, 2012 - 12:35:33 PM

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  • HAL Id : tel-00364720, version 1

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Jerome Dumont. Fouille de dynamiques multivariées, application à des données temporelles en cardiologie.. Traitement du signal et de l'image [eess.SP]. Université Rennes 1, 2008. Français. ⟨tel-00364720⟩

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