26 April 2018 Recognition of neural brain activity patterns correlated with complex motor activity
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Abstract
In this paper, based on the apparatus of artificial neural networks, a technique for recognizing and classifying patterns corresponding to imaginary movements on electroencephalograms (EEGs) obtained from a group of untrained subjects was developed. The works on the selection of the optimal type, topology, training algorithms and neural network parameters were carried out from the point of view of the most accurate and fast recognition and classification of patterns on multi-channel EEGs associated with the imagination of movements. The influence of the number and choice of the analyzed channels of a multichannel EEG on the quality of recognition of imaginary movements was also studied, and optimal configurations of electrode arrangements were obtained. The effect of pre-processing of EEG signals is analyzed from the point of view of improving the accuracy of recognition of imaginary movements.
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Semen Kurkin, Semen Kurkin, Vyacheslav Yu. Musatov, Vyacheslav Yu. Musatov, Anastasia E. Runnova, Anastasia E. Runnova, Vadim V. Grubov, Vadim V. Grubov, Tatyana Yu. Efremova, Tatyana Yu. Efremova, Maxim O. Zhuravlev, Maxim O. Zhuravlev, } "Recognition of neural brain activity patterns correlated with complex motor activity", Proc. SPIE 10717, Saratov Fall Meeting 2017: Laser Physics and Photonics XVIII; and Computational Biophysics and Analysis of Biomedical Data IV, 107171J (26 April 2018); doi: 10.1117/12.2315161; https://doi.org/10.1117/12.2315161
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