Analysis of EEG signals regularity in adults during video game play in 2D and 3D

Khairuddin, Hamizah R. and Malik, Aamir S. and Mumtaz, Wajid and Kamel, Nidal and Xia, Likun (2013) Analysis of EEG signals regularity in adults during video game play in 2D and 3D. In: 35th Annual International Conference of the IEEE EMBS, July 3 - 7, 2013, Osaka, Japan.


Official URL: http://dx.doi.org/10.1109/EMBC.2013.6609938


Video games have long been part of the entertainment industry. Nonetheless, it is not well known how video games can affect us with the advancement of 3D technology. The purpose of this study is to investigate the EEG signals regularity when playing video games in 2D and 3D modes. A total of 29 healthy subjects (24 male, 5 female) with mean age of 21.79 (1.63) years participated. Subjects were asked to play a car racing video game in three different modes (2D, 3D passive and 3D active). In 3D passive mode, subjects needed to wear a passive polarized glasses (cinema type) while for 3D active, an active shutter glasses was used. Scalp EEG data was recorded during game play using 19-channel EEG machine and linked ear was used as reference. After data were pre-processed, the signal irregularity for all conditions was computed. Two parameters were used to measure signal complexity for time series data: i) Hjorth-Complexity and ii) Composite Permutation Entropy Index (CPEI). Based on these two parameters, our results showed that the complexity level increased from eyes closed to eyes open condition; and further increased in the case of 3D as compared to 2D game play.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Signal processing in physiological systems, Time-frequency analysis of biosignals, Empirical mode decomposition in biosignal analysis
Subjects:Q Science > Q Science (General)
R Medicine > R Medicine (General)
T Technology > T Technology (General)
Academic Subject One:Academic Department - Electrical And Electronics - Communications - Digital Communications - Digital Signal Processing
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
Research Institutes > Institute for Health Analytics
ID Code:10837
Deposited By: Dr Aamir Saeed Malik
Deposited On:16 Dec 2013 23:48
Last Modified:16 Dec 2013 23:48

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