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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 a Ivo PROVAZNÍK. Testing of features for fatigue detection in EOG. \textit{BIO-MEDICAL MATERIALS AND ENGINEERING}. AMSTERDAM: IOS PRESS, 2017, roč.~28, č.~4, s.~379-392. ISSN~0959-2989. Dostupné z: https://dx.doi.org/10.3233/BME-171683.
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