Harvy, Jonathan and Thakor, Nitish and Bezerianos, Anastasios and Li, Junhua (2019) Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27 (3). pp. 358-367. DOI https://doi.org/10.1109/tnsre.2019.2893949
Harvy, Jonathan and Thakor, Nitish and Bezerianos, Anastasios and Li, Junhua (2019) Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27 (3). pp. 358-367. DOI https://doi.org/10.1109/tnsre.2019.2893949
Harvy, Jonathan and Thakor, Nitish and Bezerianos, Anastasios and Li, Junhua (2019) Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27 (3). pp. 358-367. DOI https://doi.org/10.1109/tnsre.2019.2893949
Abstract
Previous studies exploring driving drowsiness utilized spectral power and functional connectivity without considering between-frequency and more complex synchronizations. To complement such lacks, we explored inter-regional synchronizations based on the topographical and dynamic properties between frequency bands using high-order functional connectivity (HOFC) and envelope correlation. We proposed the dynamic interactions of HOFC, associated-HOFC, and a global metric measuring the aggregated effect of the functional connectivity. The EEG dataset was collected from 30 healthy subjects, undergoing two driving sessions. The two-session setting was employed for evaluating the metric reliability across sessions. Based on the results, we observed reliably significant metric changes, mainly involving the alpha band. In HOFC θα , HOFC αβ , associated-HOFC θα , and associatedHOFC αβ , the connection-level metrics in frontal-central, central-central,and central-parietal/occipitalareas were significantly increased, indicating a dominance in the central region. Similar results were also obtained in the HOFC θαβ and aHOFC θαβ . For dynamic-low-order-FC and dynamicHOFC, the global metrics revealed a reliably significant increment in the alpha, theta-alpha, and alpha-beta bands. Modularity indexes of associated-HOFC α and associatedHOFC θα also exhibited reliably significant differences. This paper demonstrated that within-band and betweenfrequency topographical and dynamic FC can provide complementary information to the traditional individual-band LOFC for assessing driving drowsiness.
Item Type: | Article |
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Uncontrolled Keywords: | Cerebral Cortex; Neural Pathways; Humans; Electroencephalography; Alpha Rhythm; Beta Rhythm; Theta Rhythm; Reproducibility of Results; Automobile Driving; Adult; Female; Male; Young Adult; Healthy Volunteers; Sleepiness |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 12 Jun 2019 09:25 |
Last Modified: | 16 May 2024 19:47 |
URI: | http://repository.essex.ac.uk/id/eprint/24715 |
Available files
Filename: Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment.pdf