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A Support System for ECG Segmentation Based on Hidden Markov Models

Julien Thomas 1 Cédric Rose 1 François Charpillet 1
1 MAIA - Autonomous intelligent machine
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Pharmaceutic studies require to analyze thousands of ECGs in order to evaluate the side effects of a new drug. In this paper we present a new support system based on the use of probabilistic models for automatic ECG segmentation. We used a bayesian HMM clustering algorithm to partition the training base, and we improved the method by using a multi-channel segmentation. We present a statistical analysis of the results where we compare different automatic methods to the segmentation of the cardiologist as a gold standard.
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Submitted on : Tuesday, September 11, 2007 - 10:46:49 AM
Last modification on : Friday, February 26, 2021 - 3:28:05 PM
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  • HAL Id : inria-00170988, version 1



Julien Thomas, Cédric Rose, François Charpillet. A Support System for ECG Segmentation Based on Hidden Markov Models. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - IEEE EMBC 2007, Aug 2007, Lyon, France. 4 p. ⟨inria-00170988⟩



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