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

arXiv: https://arxiv.org/abs/1809.06534 · HTML: https://mlsanity.com/paper/1809.06534/

## Key facts

- Cited by 32 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Sep 2018.

## Built on by (most cited first, 30 of 32)

- [LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface](https://mlsanity.com/paper/2105.02786/) (2021)
- [EEG-Deformer: A Dense Convolutional Transformer for Brain-computer Interfaces](https://mlsanity.com/paper/2405.00719/) (2024)
- [EEG-based Cross-Subject Driver Drowsiness Recognition with an Interpretable Convolutional Neural Network](https://mlsanity.com/paper/2107.09507/) (2021)
- [A Compact and Interpretable Convolutional Neural Network for Cross-Subject Driver Drowsiness Detection from Single-Channel EEG](https://mlsanity.com/paper/2106.00613/) (2021)
- [IC-U-Net: A U-Net-based Denoising Autoencoder Using Mixtures of Independent Components for Automatic EEG Artifact Removal](https://mlsanity.com/paper/2111.10026/) (2021)
- [Interpretable and Robust AI in EEG Systems: A Survey](https://mlsanity.com/paper/2304.10755/) (2023)
- [Towards Best Practice of Interpreting Deep Learning Models for EEG-based Brain Computer Interfaces](https://mlsanity.com/paper/2202.06948/) (2022)
- [A Decomposition-Based Hybrid Ensemble CNN Framework for Driver Fatigue Recognition](https://mlsanity.com/paper/2203.09477/) (2022)
- [Domain Adaptation and Generalization on Functional Medical Images: A Systematic Survey](https://mlsanity.com/paper/2212.03176/) (2022)
- [A Survey on Drowsiness Detection -- Modern Applications and Methods](https://mlsanity.com/paper/2408.12990/) (2024)
- [TDQMF: Two-dimensional quantum mass function](https://mlsanity.com/paper/2102.07652/) (2021)
- [Subject-Independent Drowsiness Recognition from Single-Channel EEG with an Interpretable CNN-LSTM model](https://mlsanity.com/paper/2112.10894/) (2021)
- [SingLEM: Single-Channel Large EEG Model](https://mlsanity.com/paper/2509.17920/) (2025)
- [Neuro-Cognitive Reward Modeling for Human-Centered Autonomous Vehicle Control](https://mlsanity.com/paper/2603.25968/) (2026)
- [A Fast Evidential Approach for Stock Forecasting](https://mlsanity.com/paper/2104.05204/) (2021)
- [Calibration-Free Driver Drowsiness Classification based on Manifold-Level Augmentation](https://mlsanity.com/paper/2212.13887/) (2022)
- [Spatio-Temporal Analysis of Transformer based Architecture for Attention Estimation from EEG](https://mlsanity.com/paper/2204.07162/) (2022)
- [An EEG Channel Selection Framework for Driver Drowsiness Detection via Interpretability Guidance](https://mlsanity.com/paper/2304.14920/) (2023)
- [Masked EEG Modeling for Driving Intention Prediction](https://mlsanity.com/paper/2408.07083/) (2024)
- [Calibration-Free EEG-based Driver Drowsiness Detection with Online Test-Time Adaptation](https://mlsanity.com/paper/2511.22030/) (2025)
- [EEG-based Classification of Drivers Attention using Convolutional Neural Network](https://mlsanity.com/paper/2108.10062/) (2021)
- [Where Is My Mind (looking at)? Predicting Visual Attention from Brain Activity](https://mlsanity.com/paper/2201.03902/) (2022)
- [EEG-Fest: Few-shot based Attention Network for Driver's Vigilance Estimation with EEG Signals](https://mlsanity.com/paper/2211.03878/) (2022)
- [Improving Generalization of Drowsiness State Classification by Domain-Specific Normalization](https://mlsanity.com/paper/2312.09461/) (2023)
- [Classification of High-dimensional Time Series in Spectral Domain using Explainable Features](https://mlsanity.com/paper/2408.08388/) (2024)
- [ART: Artifact Removal Transformer for Reconstructing Noise-Free Multichannel Electroencephalographic Signals](https://mlsanity.com/paper/2409.07326/) (2024)
- [Inter Observer Variability Assessment through Ordered Weighted Belief Divergence Measure in MAGDM Application to the Ensemble Classifier Feature Fusion](https://mlsanity.com/paper/2409.08450/) (2024)
- [Exact Fit Attention in Node-Holistic Graph Convolutional Network for Improved EEG-Based Driver Fatigue Detection](https://mlsanity.com/paper/2501.15062/) (2025)
- [Robust Spectral Fuzzy Clustering of Multivariate Time Series with Applications to Electroencephalogram](https://mlsanity.com/paper/2506.22861/) (2025)
- [Understanding Mental States in Active and Autonomous Driving with EEG](https://mlsanity.com/paper/2512.09190/) (2025)

## Abstract (arXiv)

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.