These data are part of the data sample of the paper "EEG-based approach for predicting varied human cognitive decision-making in driving". For use by editors and reviewers. This includes one compressed files: 'RAW Data.zip'. 'RAW Data.zip' includes EEG Data and driving behavior data as well as code for extracting features and training individual models. A detailed description can be found in 'Read_Me.txt'. Video footage of the experimental process of collecting driving data and EEG data is in another link (10.5281/zenodo.8093321)
This project adopted an event-related lane-departure paradigm in a virtual-reality (VR) dynamic driv...
The EEG reflects mental processes, especially modulations in the alpha and theta frequency bands are...
This document describes the analysis of Electroenchaplogram (EEG) or brain signals using computation...
These data are part of the data sample of the paper "EEG-based approach for predicting varied human ...
Distraction during driving has been recognized as a significant cause of traffic accidents. The aim ...
Introduction: EEG (electroencephalogram) has been applied as a valuable measure to estimate drivers’...
We describe driver behaviour and brain dynamics acquired from a 90-minute sustained-attention task i...
The number of older drivers is steadily increasing, and advancing age is associated with a high rate...
The human brain can be referred to as a super micro-controller, capable of managing all forms of act...
Safely operating a vehicle requires the full attention of the driver. Should the driver lose focus a...
Risky driving states such as aggressive driving and unstable driving are the cause of many traffic a...
Finding appropriate measures to trigger machine changes in an adaptive system remains a huge challen...
Finding appropriate measures to trigger machine changes in an adaptive system remains a huge challen...
The attention of drivers is a serious issue and one of the critical factors of road safety. The ques...
The aim was to assess the suitability of EEG-based techniques to recording activity during a driving...
This project adopted an event-related lane-departure paradigm in a virtual-reality (VR) dynamic driv...
The EEG reflects mental processes, especially modulations in the alpha and theta frequency bands are...
This document describes the analysis of Electroenchaplogram (EEG) or brain signals using computation...
These data are part of the data sample of the paper "EEG-based approach for predicting varied human ...
Distraction during driving has been recognized as a significant cause of traffic accidents. The aim ...
Introduction: EEG (electroencephalogram) has been applied as a valuable measure to estimate drivers’...
We describe driver behaviour and brain dynamics acquired from a 90-minute sustained-attention task i...
The number of older drivers is steadily increasing, and advancing age is associated with a high rate...
The human brain can be referred to as a super micro-controller, capable of managing all forms of act...
Safely operating a vehicle requires the full attention of the driver. Should the driver lose focus a...
Risky driving states such as aggressive driving and unstable driving are the cause of many traffic a...
Finding appropriate measures to trigger machine changes in an adaptive system remains a huge challen...
Finding appropriate measures to trigger machine changes in an adaptive system remains a huge challen...
The attention of drivers is a serious issue and one of the critical factors of road safety. The ques...
The aim was to assess the suitability of EEG-based techniques to recording activity during a driving...
This project adopted an event-related lane-departure paradigm in a virtual-reality (VR) dynamic driv...
The EEG reflects mental processes, especially modulations in the alpha and theta frequency bands are...
This document describes the analysis of Electroenchaplogram (EEG) or brain signals using computation...