Multi-channel EEG recordings during a sustained-attention driving task

TL;DR

This paper presents a comprehensive dataset of multi-channel EEG recordings during a simulated driving task designed to study sustained attention, lane departure, and driver fatigue, aiming to facilitate neural analysis and brain-computer interface development.

Contribution

The study provides a detailed, publicly available EEG dataset from a 90-minute driving simulation with lane departure events, enabling advanced research in neural dynamics and driver fatigue detection.

Findings

Dataset includes 62 EEG recordings from 27 subjects.

Data captures brain responses during lane deviations and recoveries.

Potential to develop neural markers for driving fatigue and attention.

Abstract

We described driver behaviour and brain dynamics acquired from a 90-minute sustained-attention task in an immersive driving simulator. The data include 62 copies of 32 channel electroencephalography (EEG) data for 27 subjects that drove on a four lane highway and were asked to keep the car cruising in the centre of the lane. Lane departure events were randomly induced to make the car drift from the original cruising lane towards the left or right lane. A complete trial includes events with deviation onset, response onset, and response offset. The next trial, in which the subject has to drive back to the original cruising lane, occurs from 5 to 10 seconds after finishing the current trial. We hope that this dataset will lead to the development of novel neural processing assays that can be used to index brain cortical dynamics and detect driving fatigue and drowsiness. This publicly available dataset is beneficial to the neuroscientific and brain computer interface communities.