DeepAI AI Chat
Log In Sign Up

Applications of brain imaging methods in driving behaviour research

by   Milad Haghani, et al.

Applications of neuroimaging methods have substantially contributed to the scientific understanding of human factors during driving by providing a deeper insight into the neuro-cognitive aspects of driver brain. This has been achieved by conducting simulated (and occasionally, field) driving experiments while collecting driver brain signals of certain types. Here, this sector of studies is comprehensively reviewed at both macro and micro scales. Different themes of neuroimaging driving behaviour research are identified and the findings within each theme are synthesised. The surveyed literature has reported on applications of four major brain imaging methods. These include Functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), Functional Near-Infrared Spectroscopy (fNIRS) and Magnetoencephalography (MEG), with the first two being the most common methods in this domain. While collecting driver fMRI signal has been particularly instrumental in studying neural correlates of intoxicated driving (e.g. alcohol or cannabis) or distracted driving, the EEG method has been predominantly utilised in relation to the efforts aiming at development of automatic fatigue/drowsiness detection systems, a topic to which the literature on neuro-ergonomics of driving particularly has shown a spike of interest within the last few years. The survey also reveals that topics such as driver brain activity in semi-automated settings or the brain activity of drivers with brain injuries or chronic neurological conditions have by contrast been investigated to a very limited extent. Further, potential topics in relation to driving behaviour are identified that could benefit from the adoption of neuroimaging methods in future studies.


page 8

page 14

page 15

page 27

page 28


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

Drivers cognitive and physiological states affect their ability to contr...

Real-time fMRI-based Brain Computer Interface: A Review

In recent years, the rapid development of neuroimaging technology has be...

Inferring Brain Dynamics via Multimodal Joint Graph Representation EEG-fMRI

Recent studies have shown that multi-modeling methods can provide new in...

Building Confidence in Scientific Computing Software Via Assurance Cases

Assurance cases provide an organized and explicit argument for correctne...

Detecting driver distraction using stimuli-response EEG analysis

Detecting driver distraction is a significant concern for future intelli...

Shared control schematic for brain controlled vehicle based on fuzzy logic

Brain controlled vehicle refers to the vehicle that obtains control comm...