Experimental Research for the Analysis and Classification of EEG Signals With the Aim of Identifying Brain Activity Under the Mental Calculation Tasks

This paper presents the results of some experimental studies on the electrical activity of the brain under the conditions of mental arithmetical tasks. It is known that the recognition of evoked potentials from brain bioelectrical signals is a difficult problem mainly due to the cumulative effects of brain waves and the very small level of the signal. The discrimination of states of mental activity specific to arithmetic calculation tasks in relation to the state specific to their absence is investigated by frequency analysis techniques of EEG signals and their classification by topological and temporal criteria. A Biosemi system with 64 electrodes and three basic scenarios for mental tasks that were applied several times to the same subject were used for data acquisition. Each EEG signal was filtered in the dedicated bands δ, θ, α, β, and Y. The results in this paper are based on the analysis of the spectral power obtained after processing the data for two specific bands case α,β. The evolution of the spectral peaks over time for all 64 recording signals provides a spatial temporal mapping of the electrical activity of the brain to identify the most relevant response channels and identify the most suitable conditions for discriminating mental states using a larger number of electrodes compared to other similar research reported..