| Field |
Value |
Language |
|
dc.contributor.author |
Nguyen, KH |
|
|
dc.contributor.author |
Ebbatson, M |
|
|
dc.contributor.author |
Tran, Y |
|
|
dc.contributor.author |
Craig, A |
|
|
dc.contributor.author |
Nguyen, H
https://orcid.org/0000-0003-3373-8178
|
|
|
dc.contributor.author |
Chai, R
https://orcid.org/0000-0002-1922-7024
|
|
|
dc.date.accessioned |
2024-01-16T04:35:22Z |
|
|
dc.date.available |
2023-02-19 |
|
|
dc.date.available |
2024-01-16T04:35:22Z |
|
|
dc.date.issued |
2023-02-21 |
|
|
dc.identifier.citation |
Sensors (Basel), 2023, 23, (5), pp. 2383 |
|
|
dc.identifier.issn |
1424-8220 |
|
|
dc.identifier.issn |
1424-8220 |
|
|
dc.identifier.uri |
http://hdl.handle.net/10453/174582
|
|
|
dc.description.abstract |
This study examined the brain source space functional connectivity from the electroencephalogram (EEG) activity of 48 participants during a driving simulation experiment where they drove until fatigue developed. Source-space functional connectivity (FC) analysis is a state-of-the-art method for understanding connections between brain regions that may indicate psychological differences. Multi-band FC in the brain source space was constructed using the phased lag index (PLI) method and used as features to train an SVM classification model to classify driver fatigue and alert conditions. With a subset of critical connections in the beta band, a classification accuracy of 93% was achieved. Additionally, the source-space FC feature extractor demonstrated superiority over other methods, such as PSD and sensor-space FC, in classifying fatigue. The results suggested that source-space FC is a discriminative biomarker for detecting driving fatigue. |
|
|
dc.format |
Electronic |
|
|
dc.language |
eng |
|
|
dc.publisher |
MDPI |
|
|
dc.relation.ispartof |
Sensors (Basel) |
|
|
dc.relation.isbasedon |
10.3390/s23052383 |
|
|
dc.rights |
info:eu-repo/semantics/openAccess |
|
|
dc.subject |
0301 Analytical Chemistry, 0502 Environmental Science and Management, 0602 Ecology, 0805 Distributed Computing, 0906 Electrical and Electronic Engineering |
|
|
dc.subject.classification |
Analytical Chemistry |
|
|
dc.subject.classification |
3103 Ecology |
|
|
dc.subject.classification |
4008 Electrical engineering |
|
|
dc.subject.classification |
4009 Electronics, sensors and digital hardware |
|
|
dc.subject.classification |
4104 Environmental management |
|
|
dc.subject.classification |
4606 Distributed computing and systems software |
|
|
dc.subject.mesh |
Humans |
|
|
dc.subject.mesh |
Electroencephalography |
|
|
dc.subject.mesh |
Brain |
|
|
dc.subject.mesh |
Fatigue |
|
|
dc.subject.mesh |
Computer Simulation |
|
|
dc.subject.mesh |
Automobile Driving |
|
|
dc.subject.mesh |
Brain |
|
|
dc.subject.mesh |
Humans |
|
|
dc.subject.mesh |
Fatigue |
|
|
dc.subject.mesh |
Electroencephalography |
|
|
dc.subject.mesh |
Automobile Driving |
|
|
dc.subject.mesh |
Computer Simulation |
|
|
dc.subject.mesh |
Humans |
|
|
dc.subject.mesh |
Electroencephalography |
|
|
dc.subject.mesh |
Brain |
|
|
dc.subject.mesh |
Fatigue |
|
|
dc.subject.mesh |
Computer Simulation |
|
|
dc.subject.mesh |
Automobile Driving |
|
|
dc.title |
Source-Space Brain Functional Connectivity Features in Electroencephalogram-Based Driver Fatigue Classification. |
|
|
dc.type |
Journal Article |
|
|
utslib.citation.volume |
23 |
|
|
utslib.location.activity |
Switzerland |
|
|
utslib.for |
0301 Analytical Chemistry |
|
|
utslib.for |
0502 Environmental Science and Management |
|
|
utslib.for |
0602 Ecology |
|
|
utslib.for |
0805 Distributed Computing |
|
|
utslib.for |
0906 Electrical and Electronic Engineering |
|
|
pubs.organisational-group |
/University of Technology Sydney |
|
|
pubs.organisational-group |
/University of Technology Sydney/Faculty of Engineering and Information Technology |
|
|
pubs.organisational-group |
/University of Technology Sydney/Strength - CHT - Health Technologies |
|
|
pubs.organisational-group |
/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering |
|
|
pubs.organisational-group |
/University of Technology Sydney/Centre for Health Technologies (CHT) |
|
|
utslib.copyright.status |
open_access |
* |
|
dc.date.updated |
2024-01-16T04:35:21Z |
|
|
pubs.issue |
5 |
|
|
pubs.publication-status |
Published online |
|
|
pubs.volume |
23 |
|
|
utslib.citation.issue |
5 |
|
