EEG Correlates of Driving Performance

Techniques for monitoring human performance traditionally rely on subjective responses and task-specific scoring, yet research suggests EEG could offer multiple metrics with high temporal resolution accuracy that be leveraged human–computer interaction purposes. The objective of the presented work is to investigate which correlate task evaluate whether combinations these produce effective predictive models, facilitating further understanding psychological link performance. A user study was conducted 32 participants required negotiate a driving course ambition learning improving ability during an recording session. filtered post-processed find power spectral density in alpha ( $\alpha$ ), beta notation="LaTeX">$\beta$ delta notation="LaTeX">$\delta$ theta notation="LaTeX">$\theta$ ) frequency bands, as well frontal asymmetry (FAA). initial laps were considered baseline average improvement calculated over remaining terms percentage duration track traversal. Results demonstrate event related desynchronization increased p =. 000), 000) evidence relationship between overall change FAA efficiency. full electrode analysis identifies notation="LaTeX">$\delta _{{\rm F}_{4}}$ optimal predicting collisions, efficiency best predicted by combination notation="LaTeX">$\beta O}_{\rm z}}$ .