A technical approach to map colour pixels using EEG based model

Electroencephalography (EEG) signals arise from the ionic potentials evolved when neurons are fired in the brain during a thought process. Functional Magnetic Resonance Imaging (fMRI) and EEG are two of the commonly used techniques for mapping brain activity and gaining a window into our thoughts. T...

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Bibliographic Details
Published in2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS) pp. 70 - 74
Main Authors Anupama, H. S., Soumya, Mahalakshmi A., Tyagi, Sudarshini, Cauvery, N. K., Lingaraju, G. M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2016
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Summary:Electroencephalography (EEG) signals arise from the ionic potentials evolved when neurons are fired in the brain during a thought process. Functional Magnetic Resonance Imaging (fMRI) and EEG are two of the commonly used techniques for mapping brain activity and gaining a window into our thoughts. The possibilities are endless, if a technique is devised to understand exactly what a person is thinking. The aim of this paper is to propose and validate the findings of our research on identifying an image that a subject visualizes in his mind. Theoretically, fMRI is suited for this purpose. However, owing to the bulky, expensive and time consuming nature of fMRI, the proposed model uses EEG signals. Owing to the fact that any picture is made of Red, Blue and Green pixels, subjects were asked to visualize Red, Green and Blue colors, and the corresponding EEG signals were captured. The obtained results showed convincing consistency by being same across subjects for each color, and by showing remarkable difference in the patterns for different colors. These findings can be extrapolated to map an entire picture visualized in the brain. Therefore, the findings of this paper realizes the upcoming potential of EEG as it is a cost effective, less bulky and time saving solution, which still provides convincing results.
ISBN:1509010203
9781509010202
DOI:10.1109/CSITSS.2016.7779442