Patterns recognition of electric brain activity using artificial neural networks

V. Yu. Musatov; S. V. Pchelintseva; A. E. Runnova; A. E. Hramov

doi:10.1117/12.2267701

14 April 2017 Patterns recognition of electric brain activity using artificial neural networks

V. Yu. Musatov, S. V. Pchelintseva, A. E. Runnova, A. E. Hramov

Proceedings Volume 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III; 1033714 (2017) https://doi.org/10.1117/12.2267701
Event: Saratov Fall Meeting 2016: Fourth International Symposium on Optics and Biophotonics, 2016, Saratov, Russian Federation

Abstract

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Citation Download Citation

V. Yu. Musatov, S. V. Pchelintseva, A. E. Runnova, and A. E. Hramov "Patterns recognition of electric brain activity using artificial neural networks", Proc. SPIE 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III, 1033714 (14 April 2017); https://doi.org/10.1117/12.2267701

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