Publication detail

Testing of features for fatigue detection in EOG

NĚMCOVÁ, A. JANOUŠEK, O. VÍTEK, M. PROVAZNÍK, I.

Original Title

Testing of features for fatigue detection in EOG

Type

journal article in Web of Science

Language

English

Original Abstract

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.

Keywords

Biopac, blink, electrooculography, REM, scenes, SEM

Authors

NĚMCOVÁ, A.; JANOUŠEK, O.; VÍTEK, M.; PROVAZNÍK, I.

Released

30. 8. 2017

Publisher

IOS Press

ISBN

0959-2989

Periodical

BIO-MEDICAL MATERIALS AND ENGINEERING

Year of study

28

Number

4

State

Kingdom of the Netherlands

Pages from

379

Pages to

392

Pages count

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"
}