Microsleep Classifier Using EOG Channel Recording: A Feasibility Study

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00234350" target="_blank" >RIV/68407700:21230/15:00234350 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-22741-2_10" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-22741-2_10</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-22741-2_10" target="_blank" >10.1007/978-3-319-22741-2_10</a>

Result language
angličtina
Original language name
Microsleep Classifier Using EOG Channel Recording: A Feasibility Study
Original language description
The microsleeps (MS) cause many accidents and can have a huge social impact. Automated prediction or early detection of the MS states could help to monitor level of fatigue. An automated MS classifier based on the EOG signal is proposed. There were analysed 28 episodes of MS. We observed slow eye movements without rapid changes during MS episodes. An automated feature extraction and classification using EOG channels showed promising results (sensitivity 93 %, positive predictivity 57 %). To confirm thehypothesis it is crucial to extend the study and to analyse larger amount of MS data.
Czech name
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Czech description
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Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Information Technology in Bio- and Medical Informatics (6th)
ISBN
978-3-319-22740-5
ISSN
0302-9743
e-ISSN
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Number of pages
5
Pages from-to
109-113
Publisher name
Springer International Publishing
Place of publication
Cham
Event location
Valencia
Event date
Sep 3, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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