Abstract
Electroencephalogram (EEG) is a research subject that has been studied constantly. By the analysis of EEG signals, the mental state of the humans can be detected, so it would contribute to the design of human-machine interaction (HMI) systems. In this paper, we intend to study the cognitive state using EEG signals when the subject is performing a visual search task. We tried to obtain the different patterns of the EEG signals when the subject is performing differently in the task. Several pattern recognition algorithms on the signal are conducted to find the principal features in the EEG signals. We can see that the features of EEG signals can present the differences between cognitive states and this result will be beneficial to the recognition of the cognitive state of the operators in the complex systems.
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Zhang, S., Lu, Y., Fu, S. (2020). Recognition of the Cognitive State in the Visual Search Task. In: Ayaz, H. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2019. Advances in Intelligent Systems and Computing, vol 953. Springer, Cham. https://doi.org/10.1007/978-3-030-20473-0_35
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DOI: https://doi.org/10.1007/978-3-030-20473-0_35
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