J 2017

Testing of features for fatigue detection in EOG

NĚMCOVÁ, Andrea, Oto JANOUŠEK, Martin VITEK a Ivo PROVAZNÍK

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

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

UT WoS

000408296300005

Klíčová slova anglicky

Biopac; blink; electrooculography; REM; scenes; SEM

Štítky

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 20. 3. 2018 18:40, Soňa Böhmová

Anotace

V originále

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.