Abstract: Results concerning detection of the P300 wave in EEG segments using scalar products with signals of various shapes are presented and their advantages and limitations are discussed. From the point of view of the computational complexity, the proposed algorithm is a simple algorithm, based on a scalar product and searching for the max value of 6 calculated values. Because we considered that the human subject is not a robot that precisely generates P300 and that there is also a human component of error in the involuntary generation of such waves, we have also calculated the rate of classification of character in the human visual field. To validate the proposed method, electroencephalography recordings from the competition for Spelling BCI Competition III Challenge 2005 -Dataset II have been used.

Monica Fira, Liviu Goras and Anca Lazar, “On P300 Detection using Scalar Products” International Journal of Advanced Computer Science and Applications(IJACSA), 9(1), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090113

@article{Fira2018,
title = {On P300 Detection using Scalar Products},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090113},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090113},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {1},
author = {Monica Fira and Liviu Goras and Anca Lazar}
}