Brain-Computer Interface and Neurointerface Technologies for Control with Robotic Devices

Duhaidahawi Murtadha Ahmed  Luti; Dheyab Salman  Ibrahim; Tomashevsky Yuliy  Boleslavovich

Duhaidahawi Murtadha Ahmed Luti Postgraduate, Saratov State Technical University named after Gagarin Yu.A
Dheyab Salman Ibrahim Professor of Operations Research Diyala University
Tomashevsky Yuliy Boleslavovich Professor of Technical Sciences, Saratov State Technical University named after Yu.A.

Keywords: Robotic Mechanisms, Electroencephalogram (EEG) Pattern Recognition, Brain Rhythms, Artificial Neural Networks, Neurointerface

Abstract

The object of the study is the neural interfaces that control ro- botic devices using signals of brain origin recorded by electroencephalography. The subject of the study is the methods and algorithms for recognizing EEG patterns corresponding to the image of an imaginary motor team subject. The aim of the work is to develop a software and hardware complex for controlling robotic mechanisms, which allows to recognize EEG patterns of motor activity and adapt to a specific operator. Materials and methods.To solve the tasks in the work, methods of processing time series and creating artificial neural networks were used. Results. A device is proposed that is implemented on the platform of an analog-to-digital recorder such as Arduino uno. The device allows you to recognize EEG signals of brain activity and generate signals for controlling robotic mechanisms such as bionic prostheses, robotic wheelchairs, exoskeletons. Conclusions. Using the proposed device will allow people suffering from serious disorders of the motor system to improve their quality of life.

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