Using Hierarchical Clustering for Newborn EEG Signal Classification

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00160966" target="_blank" >RIV/68407700:21230/09:00160966 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21460/09:00160966

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Using Hierarchical Clustering for Newborn EEG Signal Classification

Original language description

This paper addresses automated classification of newborn sleep electroencephalogram (EEG) using hierarchical clustering. Newborn EEG plays an important role in determining the maturity level of neonatal brain. For accurate classification it is necessaryto determine and/or calculate the most informative features. In our approach we use a method based on power spectral density (PSD) applied to each EEG channel. We also use features derived from EOG; EMG; ECG and PNG signals. The goal of the classifiers was to separate different classes of the PSG recording correctly (and minimize the classification error).

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

<a href="/en/project/1ET101210512" target="_blank" >1ET101210512: Intelligent methods for evaluation of long-term EEG recordings</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2009

Confidentiality

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

Article name in the collection

Workshop 09

ISBN

978-80-01-04286-1

ISSN

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e-ISSN

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Number of pages

2

Pages from-to

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Publisher name

ČVUT

Place of publication

Praha

Event location

Praha

Event date

Feb 16, 2009

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

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