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@article{1392196,
author = {Němcová, Andrea and Janoušek, Oto and Vitek, Martin and Provazník, Ivo},
article_location = {AMSTERDAM},
article_number = {4},
doi = {http://dx.doi.org/10.3233/BME-171683},
keywords = {Biopac; blink; electrooculography; REM; scenes; SEM},
language = {eng},
issn = {0959-2989},
journal = {BIO-MEDICAL MATERIALS AND ENGINEERING},
title = {Testing of features for fatigue detection in EOG},
volume = {28},
year = {2017}
}
TY - JOUR
ID - 1392196
AU - Němcová, Andrea - Janoušek, Oto - Vitek, Martin - Provazník, Ivo
PY - 2017
TI - Testing of features for fatigue detection in EOG
JF - BIO-MEDICAL MATERIALS AND ENGINEERING
VL - 28
IS - 4
SP - 379-392
EP - 379-392
PB - IOS PRESS
SN - 09592989
KW - Biopac
KW - blink
KW - electrooculography
KW - REM
KW - scenes
KW - SEM
N2 - 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.
ER -
NĚMCOVÁ, Andrea, Oto JANOUŠEK, Martin VITEK and Ivo PROVAZNÍK. Testing of features for fatigue detection in EOG. \textit{BIO-MEDICAL MATERIALS AND ENGINEERING}. AMSTERDAM: IOS PRESS, 2017, vol.~28, No~4, p.~379-392. ISSN~0959-2989. Available from: https://dx.doi.org/10.3233/BME-171683.
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