Citation

Toa, Chean Khim and Sim, Kok Swee and Tan, Shing Chiang (2021) Application of Mixed Reality and Electroencephalogram in Brain Attentive Level. In: 2nd FET PG Engineering Colloquium Proceedings 2021, 1-15 Dec. 2021, Online Conference. (Unpublished)

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Abstract

In this project, a Mixed Reality (MR) application and Electroencephalogram (EEG) will be used to classify whether a person is being attentive or distracted. MR applications are unique in that they project virtual information into the user’s real environment. This blend of real and virtual changes the level of impact and persuasive power of the experience. Since MR is a new-wave technology, there is room to explore the potential of MR in the attention-related research field. An EEG is an electrophysiological monitoring test where it measures the electrical activity in the brain. The EEG data can provide valuable quantitative and unbiased information on brain activity in a millisecond timeframe. The main goal of this research involves the design of a framework for visual search tests with the use of MR and to propose a deep learning model for attention and distraction classification. The use of visual search tests is to induce human attention and distraction. During this period, the EEG signal of the users will be recorded in a millisecond timeframe. After that, a deep learning method named Convolution Attention Memory Neural Network (CAMNN) will be proposed to perform the attention distraction classification of EEG signals.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Cognitive, Deep learning, Electroencephalogram, Mixed Reality, Visual search, Machine Learning
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Engineering and Technology (FET) Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	28 Jan 2022 00:37
Last Modified:	24 Feb 2023 06:02
URII:	http://shdl.mmu.edu.my/id/eprint/9896

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