Analyzing and Monitoring of People’s Attention from EEG Signals

International Journal of Electrical and Electronics Engineering

© 2024 by SSRG - IJEEE Journal

Volume 11 Issue 3

Year of Publication : 2024

Authors : T. Manoj Prasath, R. Vasuki

10.14445/23488379/IJEEE-V11I3P104

How to Cite?

T. Manoj Prasath, R. Vasuki, "Analyzing and Monitoring of People’s Attention from EEG Signals," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 3, pp. 42-64, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I3P104

Abstract:

The human brain is made up of millions of neurons which are responsible for the regulation of motor and sensory events. Analyzing brain signals or images can help one understand the cognitive behaviour of the brain. On earth, psychologists often think about reading EEG signals in order to get a typical analysis of an individual. Yet, it can be pretty challenging and varies from person to person to comprehend how an individual behaves and responds to the numerous orders set up for them. This research is prone to an experimental take away of the personage’s electroencephalographic waveform, retrieving the unusually fluctuating curves over suspected guidelines during the complete examination. EEG fluctuations play a significant role in this procedure because it is possible to distinguish crucial details specifically from the waveform. With the assistance of a connected set of probes, an impotent lead, an EEG kit, and the patient being evaluated, this intervention is carried out automatically. This work analyses the attention from EEG signals obtained. A proprietary eSense algorithm was designed to calculate attention. To verify the proposed algorithm, an application was created, which was used in the experiment itself. Next, an analysis of the results and progress of the different phases was carried out based on the data obtained from the measurements. Finally, the overall success of the proposed algorithm was evaluated, and the strengths and weaknesses of the chosen approach were discussed. The calculated values were compared with those from the headband to check whether the “eSense” algorithm matches methods based on traditional techniques.

Keywords:

Brain states, Electroencephalogram (EEG), Fluctuating curves, Nervous system, eSense algorithm.

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