Detection of myocardial ischemia with hidden Semi-Markovian models

Jérôme Dumont 1, * Guy Carrault 2 Pedro Gomis 3 Gallen Wagner 4 Alfredo Hernandez 2, *
* Auteur correspondant
1 LTSI - Laboratoire Traitement du Signal et de l'Image
2 LTSI - Laboratoire Traitement du Signal et de l'Image
3 ESAII - Enginyeria de Sistemes, Automàtica i Inf.Ind.
4 Duke Division of Cardiology
Abstract : A new method for myocardial ischemia detection is proposed in this communication. The originality of this method relies on the analysis of the dynamics of times series extracted from the ECG, whereas traditional methods are based on static decision rules. After the extraction of a feature vector, from ECG signals from the STAFF3 database, the dynamics are characterised with an Hidden Semi-Markovian Model (HSMM). The ischemic detector uses a reference HSMM and an ischemic HSMM and then compare the log-likelihood of the time series. Results obtained with percutaneous transluminal coronary angioplasty (PTCA) records of the STAFF3 database show an improved detection rate (96% of sensibility and 80% of specificity) with respect to other methods applied on the same database.
Keywords : ECG PTCA record STAFF3 database detection rate feature vector extraction hidden semiMarkovian models ischemic HSMM log-likelihood myocardial ischemia detection percutaneous transluminal coronary angioplasty record reference HSMM sensibility specificity static decision rules times series
Type de document :
Communication dans un congrès
Computers In Cardiology, Sep 2009, Park City, UT, United States. IEEE, pp.121 - 124, 2010
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http://www.hal.inserm.fr/inserm-00530935
Contributeur : Lotfi Senhadji <>
Soumis le : dimanche 31 octobre 2010 - 11:07:58
Dernière modification le : mercredi 16 mai 2018 - 11:23:40
Document(s) archivé(s) le : mardi 1 février 2011 - 11:05:36

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Jérôme Dumont, Guy Carrault, Pedro Gomis, Gallen Wagner, Alfredo Hernandez. Detection of myocardial ischemia with hidden Semi-Markovian models. Computers In Cardiology, Sep 2009, Park City, UT, United States. IEEE, pp.121 - 124, 2010. 〈inserm-00530935〉

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