Systems and Means of Informatics
2022, Volume 32, Issue 3, pp 36-49
CLASSIFICATION MODELS FOR P300 EVOKED POTENTIALS
- A. M. Samokhina
- R. G. Neychev
- V. V. Goncharenko
- R. K. Grigoryan
- V. V. Strijov
Abstract
The paper is devoted to the problem of user's attention detection.
It investigates the choice of a visual stimulus by the electroencephalogram (EEG) with the evoked potentials related to the event, P300, highlighted in it. The electrical brain potentials are measured while the user is observing visual stimuli. The goal is to select a stimulus which causes the maximum brain response. A classification model detects if there is a P300 potential in an EEG segment. Various classification models for event-related potentials are compared.
The paper proposes a method of data augmentation to improve the quality of classification. Computational experiments use an original real-world dataset of P300 potentials. This dataset was collected on 60 healthy users who are presented with visual stimuli. It is released to the public access.
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[+] About this article
Title
CLASSIFICATION MODELS FOR P300 EVOKED POTENTIALS
Journal
Systems and Means of Informatics
Volume 32, Issue 3, pp 36-49
Cover Date
2022-06-11
DOI
10.14357/08696527220304
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
classification; electroencephalogram; event-related potential; model selection; brain-computer interface
Authors
A. M. Samokhina  , R. G. Neychev , V. V. Goncharenko , R. K. Grigoryan  , and V. V. Strijov 
Author Affiliations
Moscow Institute of Physics and Technology, 9 Institutskiy Per., Dolgoprudny, Moscow Region 141700, Russian Federation
M. V. Lomonosov Moscow State University, 1 Leninskie Gory, GSP-1, Moscow 119991, Russian Federation
Federal Research Center "Computer Science and Control", Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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