A Support System for ECG Segmentation Based on Hidden Markov Models

Julien Thomas; Cédric Rose; François Charpillet

inria-00170988, version 1

A Support System for ECG Segmentation Based on Hidden Markov Models

Julien Thomas^a^, 1, Cédric Rose () ¹, François Charpillet () ¹

29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - IEEE EMBC 2007 (2007) 4 pages

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.

a – Cardiabase
1: MAIA (INRIA Lorraine - LORIA)
INRIA – CNRS : UMR7503 – Université Henri Poincaré - Nancy I – Université Nancy II – Institut National Polytechnique de Lorraine (INPL)

inria-00170988, version 1
http://hal.inria.fr/inria-00170988
oai:hal.inria.fr:inria-00170988
From: Cédric Rose <>
Submitted on: Tuesday, 11 September 2007 10:46:49
Updated on: Wednesday, 19 September 2007 11:16:58

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