Silent EEG-Speech Recognition Using Convolutional and Recurrent Neural Network with 85% Accuracy of 9 Words Classification

Silent EEG-Speech Recognition Using Convolutional and Recurrent Neural Network with 85% Accuracy of 9 Words Classification

In this work, we focus on silent speech recognition in electroencephalography (EEG) data of healthy individuals to advance brain–computer interface (BCI) development to include people with neurodegeneration and movement and communication difficulties in society. Our dataset was recorded from 270 hea...

Full description

Bibliographic Details
Main Authors: Darya Vorontsova, Ivan Menshikov, Aleksandr Zubov, Kirill Orlov, Peter Rikunov, Ekaterina Zvereva, Lev Flitman, Anton Lanikin, Anna Sokolova, Sergey Markov, Alexandra Bernadotte
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Sensors
Subjects:
brain–computer interface
neurorehabilitation
neurodegeneration
neurodegeneration treatment
senescence
eSports
Online Access:https://www.mdpi.com/1424-8220/21/20/6744

Internet

https://www.mdpi.com/1424-8220/21/20/6744

Similar Items