Detail publikace

Testing of features for fatigue detection in EOG

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

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"
}