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

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.

This manuscript is submitting to Nature: Scientific Data

References in corpus (2)

• Driver Drowsiness Estimation from EEG Signals Using Online Weighted Adaptation Regularization for Regression (OwARR)
• Dynamically Weighted Ensemble-based Prediction System for Adaptively Modeling Driver Reaction Time

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