A Survey and Tutorial of EEG-Based Brain Monitoring for Driver State Analysis

by   Ce Zhang, et al.

Drivers cognitive and physiological states affect their ability to control their vehicles. Thus, these driver states are important to the safety of automobiles. The design of advanced driver assistance systems (ADAS) or autonomous vehicles will depend on their ability to interact effectively with the driver. A deeper understanding of the driver state is, therefore, paramount. EEG is proven to be one of the most effective methods for driver state monitoring and human error detection. This paper discusses EEG-based driver state detection systems and their corresponding analysis algorithms over the last three decades. First, the commonly used EEG system setup for driver state studies is introduced. Then, the EEG signal preprocessing, feature extraction, and classification algorithms for driver state detection are reviewed. Finally, EEG-based driver state monitoring research is reviewed in-depth, and its future development is discussed. It is concluded that the current EEG-based driver state monitoring algorithms are promising for safety applications. However, many improvements are still required in EEG artifact reduction, real-time processing, and between-subject classification accuracy.


page 2

page 3


EEG-Fest: Few-shot based Attention Network for Driver's Vigilance Estimation with EEG Signals

A lack of driver's vigilance is the main cause of most vehicle crashes. ...

An active approach towards monitoring and enhancing drivers' capabilities – the ADAM cogtec solution

Driver's cognitive ability at a given moment is the most elusive variabl...

Dynamically Weighted Ensemble-based Prediction System for Adaptively Modeling Driver Reaction Time

Predicting a driver's cognitive state, or more specifically, modeling a ...

Applications of brain imaging methods in driving behaviour research

Applications of neuroimaging methods have substantially contributed to t...

The Application of Driver Models in the Safety Assessment of Autonomous Vehicles: A Survey

Driver models play a vital role in developing and verifying autonomous v...

Driver fatigue EEG signals detection by using robust univariate analysis

Driver fatigue is a major cause of traffic accidents and the electroence...

Please sign up or login with your details

Forgot password? Click here to reset