Abstract
This paper covers the initial research and analysis of the EEG signal for the purpose of designing a neural interface for identification of the mental state. Such neural interface can be beneficial in various fields of automation and industry and can also potentially serve as a safety feature for safety critical processes. In the first section of this paper we discuss the performed experiment and also the technical means for the EEG data acquisition. In following chapter, we are describing the data itself and we are also performing the basic data analysis as well as the correlation identification. Final part of this paper we are evaluating our hypothesis to finding correlations in the dataset.
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