Morphology Analysis of Physiological Signals Using Hidden Markov Models

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F04%3A03099574" target="_blank" >RIV/68407700:21230/04:03099574 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Morphology Analysis of Physiological Signals Using Hidden Markov Models

Original language description

We describe a clustering algorithm based on continuous Hidden Markov Models (HMM) to automatically classify both electrocardiogram (ECG) and intracranial pressure (ICP) beats based on their morphology. The algorithm detects, classifies and labels each beat based on morphology. In order to avoid the numerical problems with classical Expectation-Maximization (EM) algorithm we apply a novel method of simulated annealing (SIM) for HMM optimization. We show that better results are achieved using simulated annealing approach.

Czech name

Není k dispozici

Czech description

Není k dispozici

Type

A - Audiovisual production

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2004

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

ISBN

0-7695-2128-2

Place of publication

London

Publisher/client name

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Version

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Carrier ID

neuvedeno