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A Support System for ECG Segmentation Based on Hidden Markov Models
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.
Cited literature [9 references]
https://hal.inria.fr/inria-00170988
Contributor : Cédric Rose Connect in order to contact the contributor
Submitted on : Tuesday, September 11, 2007 - 10:46:49 AM
Last modification on : Friday, February 26, 2021 - 3:28:05 PM
Long-term archiving on: : Friday, April 9, 2010 - 1:52:51 AM
Contributor : Cédric Rose Connect in order to contact the contributor
Submitted on : Tuesday, September 11, 2007 - 10:46:49 AM
Last modification on : Friday, February 26, 2021 - 3:28:05 PM
Long-term archiving on: : Friday, April 9, 2010 - 1:52:51 AM
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thomas-rose-07.pdf
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