Naslov
Gender Differences in EEG Features While Driving

Autori
Stančin, Igor ; Friganović, Krešimir ; Zelenika Zeba, Mirta ; Jović, Alan ; Cifrek, Mario

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 2nd International Conference on Advances in Signal Processing and Artificial Intelligence / Yurish, Sergey Y. - Barcelona : International Frequency Sensor Association (IFSA), 2020, 125-130

ISBN
978-84-09-21931-5

Skup
Advances in Signal Processing and Artificial Intelligence (ASPAI 2020)

Mjesto i datum
Berlin, Njemačka, 18.11.2020. - 20.11.2020

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
gender difference ; EEG features ; driving ; recurrence quantification analysis

Sažetak
Gender differences in traffic are generally analyzed through the number of accidents reported to the police. Our research aims to observe gender differences in electroencephalographical signals (EEG) while participants are driving. Time-frequency domain features and recurrence quantification analysis (RQA) features are calculated in order to analyze the differences. To compare male and female drivers, we used Mann–Whitney U test and compared correlations between features and brain regions. Female drivers showed significantly higher beta relative power in the occipital right region and significantly higher alpha relative power in the frontal regions, while male drivers showed significantly higher theta relative power in all regions except in the front right region. Most RQA features show a significant difference between male and female drivers. Also, male drivers showed significantly higher correlations between the RQA features, especially between different brain regions. These results could reflect the differences in the information processing strategies of male and female drivers, e.g. they tend to focus on different information when performing the task. That could account for reported gender differences in the number of traffic accidents and traffic behavior.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Kognitivna znanost (prirodne, tehničke, biomedicina i zdravstvo, društvene i humanističke znanosti)

POVEZANOST RADA