TY - GEN
T1 - Graph theoretical analysis of EEG functional network during multi-workload flight simulation experiment in virtual reality environment
AU - Zhang, Shengqian
AU - Zhang, Yuan
AU - Sun, Yu
AU - Thakor, Nitish
AU - Bezerianos, Anastasios
N1 - Funding Information:
This work is supported partially by the National University of Singapore under the grant number of R-719-001-102-232 and the Ministry of Education of Singapore under the grant number of MOE2014-T2-1-115. Asterisk indicates corresponding author.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/13
Y1 - 2017/9/13
N2 - The research field of mental workload has attracted abundant researchers as mental workload plays a crucial role in real-life performance and safety. While previous studies have examined the neural correlates of mental workload in 2D scenarios (i.e., presenting stimuli on a computer screen (CS) environment using univariate methods (e.g., EEG channel power), it is still unclear of the findings of one that uses multivariate approach using graphical theory and the effects of a 3D environment (i.e., presenting stimuli on a Virtual Reality (VR)). In this study, twenty subjects undergo flight simulation in both CS and VR environment with three stages each. After preprocessing, the Electroencephalogram (EEG) signals were a connectivity matrix based on Phase Lag Index (PLI) will be constructed. Graph theory analysis then will be applied based on their global efficiency, local efficiency and nodal efficiency on both alpha and theta band. For global efficiency and local efficiency, VR values are generally lower than CS in both bands. For nodal efficiency, the regions that show at least marginally significant decreases are very different for CS and VR. These findings suggest that 3D simulation effects a higher mental workload than 2D simulation and that they each involved a different brain region.
AB - The research field of mental workload has attracted abundant researchers as mental workload plays a crucial role in real-life performance and safety. While previous studies have examined the neural correlates of mental workload in 2D scenarios (i.e., presenting stimuli on a computer screen (CS) environment using univariate methods (e.g., EEG channel power), it is still unclear of the findings of one that uses multivariate approach using graphical theory and the effects of a 3D environment (i.e., presenting stimuli on a Virtual Reality (VR)). In this study, twenty subjects undergo flight simulation in both CS and VR environment with three stages each. After preprocessing, the Electroencephalogram (EEG) signals were a connectivity matrix based on Phase Lag Index (PLI) will be constructed. Graph theory analysis then will be applied based on their global efficiency, local efficiency and nodal efficiency on both alpha and theta band. For global efficiency and local efficiency, VR values are generally lower than CS in both bands. For nodal efficiency, the regions that show at least marginally significant decreases are very different for CS and VR. These findings suggest that 3D simulation effects a higher mental workload than 2D simulation and that they each involved a different brain region.
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U2 - 10.1109/EMBC.2017.8037722
DO - 10.1109/EMBC.2017.8037722
M3 - Conference contribution
C2 - 29060763
AN - SCOPUS:85032200370
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 3957
EP - 3960
BT - 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
Y2 - 11 July 2017 through 15 July 2017
ER -