TY  - JOUR
PY  - 2023//
TI  - Neurophysiological predictors of self-reported difficulty in a virtual-reality driving scenario
JO  - Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
A1  - Ma, Jia Li
A1  - Koorathota, Sharath
A1  - Sajda, Paul
SP  - 1
EP  - 4
VL  - 2023
IS  - 
N2  - Our perception of subjective difficulty in complex tasks, such as driving, is a judgment that is likely a result of dynamic interactions between distributed brain regions. In this paper, we investigate how neurophysiological markers associated with arousal state are informative of this perceived difficulty throughout a driving task. We do this by classifying subjective difficulty reports of subjects using set of features that include neural, autonomic, and eye behavioral markers. We subsequently assess the importance of these features in the classification. We find that though multiple EEG linked to cognitive control and, motor performance linked to classification of subjective difficulty, only pupil diameter, a measure of pupil-linked arousal, is strongly linked to both measured self-reported difficulty and actual task performance. We interpret our findings in the context of arousal pathways influencing performance and discuss their relevance to future brain-computer interface systems.<p />  <p>Language: en</p>
LA  - en
SN  - 2375-7477
UR  - http://dx.doi.org/10.1109/EMBC40787.2023.10340597
ID  - ref1
ER  -