DocumentCode
3583700
Title
Wavelet and HMM association for ECG segmentation
Author
Le Page, Ronan ; Provost, Karine ; Boucher, Jean-Marc ; Cornily, Jean-Christophe ; Blanc, Jean-Jacques
Author_Institution
Dpt. Signal et Communications, École Nationale Supérieure des Télécommunications de Bretagne, Technopôle Brest Iroise, BP 832, 29285 Brest, France
fYear
2000
Firstpage
1
Lastpage
4
Abstract
This paper presents a multiscale Hidden Markov Model (HMM) to improve an automatic segmentation of an electrocardiographic signal (ECG). While the HMM describes the dynamical mean evolution of cardiac cycle, the use of wavelet analysis in association with the HMM leads to take into account local singularities and to obtain better segmentation results. This was tested on a learning base composed of 130 patients.
Keywords
Correlation; Electrocardiography; Hidden Markov models; Manuals; Signal resolution; Standards; Wavelet coefficients;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Conference, 2000 10th European
Print_ISBN
978-952-1504-43-3
Type
conf
Filename
7075604
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