Testing of features for fatigue detection in EOG

NĚMCOVÁ, Andrea, Oto JANOUŠEK, Martin VITEK a Ivo PROVAZNÍK. Testing of features for fatigue detection in EOG. 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.

Základní údaje

• Originální název: Testing of features for fatigue detection in EOG
• Autoři: NĚMCOVÁ, Andrea (203 Česká republika), Oto JANOUŠEK (203 Česká republika), Martin VITEK (203 Česká republika) a Ivo PROVAZNÍK (203 Česká republika, garant, domácí).
• Vydání: BIO-MEDICAL MATERIALS AND ENGINEERING, AMSTERDAM, IOS PRESS, 2017, 0959-2989.

Další údaje

• Originální jazyk: angličtina
• Typ výsledku: Článek v odborném periodiku
• Obor: 20601 Medical engineering
• Stát vydavatele: Nizozemské království
• Utajení: není předmětem státního či obchodního tajemství
• Impakt faktor: Impact factor: 0.872
• Kód RIV: RIV/00216224:14110/17:00097867
• Organizační jednotka: Lékařská fakulta
• Doi: http://dx.doi.org/10.3233/BME-171683
• UT WoS: 000408296300005
• Klíčová slova anglicky: Biopac; blink; electrooculography; REM; scenes; SEM
• Štítky: EL OK
• Příznaky: Mezinárodní význam, Recenzováno

Anotace

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.