Detection of sleep stages in neonatal EEG records

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F17%3A00315842" target="_blank" >RIV/68407700:21460/17:00315842 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21730/17:00315842 RIV/00023752:_____/17:43919192

Result on the web

<a href="https://link.springer.com/chapter/10.1007/978-981-10-5122-7_63" target="_blank" >https://link.springer.com/chapter/10.1007/978-981-10-5122-7_63</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-981-10-5122-7_63" target="_blank" >10.1007/978-981-10-5122-7_63</a>

Result language

angličtina

Original language name

Detection of sleep stages in neonatal EEG records

Original language description

The aim of this study is the detection of changes in sleep stages in EEG recordings in full-term and preterm newborns. We use a k-NN algorithm as a method of classification. The novelty of our approach lies in semi-automatic etalon (prototype) selection with combination of temporal analysis for sleep stages detection. The semi-automated etalon extraction includes the k-means algorithm for etalons suggestion and an expert-in-the-loop for verification of these etalons. The semi-automated approach improves significantly the time spent on the etalon selection (extraction) by the expert. The whole procedure of EEG signal processing consists of adaptive segmentation, feature extraction, semi-automatic etalon selection using k-means and expert-in-the-loop, classification using k-NN algorithm and temporal profile analysis that is able to detect the neonatal sleep stages for the full-term and even for the preterm neonates, which makes it a unique detection method.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA17-20480S" target="_blank" >GA17-20480S: Temporal context in analysis of long-term non-stationary multidimensional signal</a><br>

Continuities

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

Publication year

2017

Confidentiality

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

Article name in the collection

IFMBE Proceedings

ISBN

978-981-10-5121-0

ISSN

1680-0737

e-ISSN

1433-9277

Number of pages

4

Pages from-to

250-253

Publisher name

Springer Nature Singapore Pte Ltd.

Place of publication

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Event location

Tampere

Event date

Jun 11, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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