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NĚMCOVÁ, A. JANOUŠEK, O. VÍTEK, M. PROVAZNÍK, I.
Originální název
Testing of features for fatigue detection in EOG
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
The article deals with the testing of features for fatigue detection in electrooculography (EOG) records. An optimal methodology for EOG signal acquisition is described; the Biopac data acquisition system was used. EOG signals were being recorded while 10 volunteers were watching prepared scenes. Three scenes were created for this purpose – a rotating ball, a video of driving a car, and a cross. Recorded EOG signals were processed and 20 features were extracted. The features involved blinks, slow eye movement (SEM), rapid eye movement (REM), eye instability, magnitude, and periodicity. These features were statistically tested and discussed in terms of fatigue detection ability. Some of the features were compared with published results. Finally, the best features – fatigue indicators – were selected.
Klíčová slova
Biopac, blink, electrooculography, REM, scenes, SEM
Autoři
NĚMCOVÁ, A.; JANOUŠEK, O.; VÍTEK, M.; PROVAZNÍK, I.
Vydáno
30. 8. 2017
Nakladatel
IOS Press
ISSN
0959-2989
Periodikum
BIO-MEDICAL MATERIALS AND ENGINEERING
Ročník
28
Číslo
4
Stát
Nizozemsko
Strany od
379
Strany do
392
Strany počet
14
URL
http://content.iospress.com/journals/bio-medical-materials-and-engineering/28/4
BibTex
@article{BUT138043, author="Andrea {Němcová} and Oto {Janoušek} and Martin {Vítek} and Valentine {Provazník}", title="Testing of features for fatigue detection in EOG", journal="BIO-MEDICAL MATERIALS AND ENGINEERING", year="2017", volume="28", number="4", pages="379--392", doi="10.3233/BME-171683", issn="0959-2989", url="http://content.iospress.com/journals/bio-medical-materials-and-engineering/28/4" }