NEUROINTERFACE FOR CONTROLLING ROBOTIC DEVICES 

Bodin Oleg Nikolaevich, doctor of technical sciences, professor, sub-department of information-measuring equipment and metrology, Penza State University (40 Krasnaya street, Penza, Russia), E-mail: iit@pnzgu.ru
Solodimova Galina Anatolyevna, candidate of technical sciences, associate professor, sub-department of information-measuring equipment and metrology, Penza State University (40 Krasnaya street, Penza, Russia), E-mail: solodimova@mail.ru
Spirkin Andrei Nikolaevich, postgraduate student, Penza State University (40 Krasnaya street, Penza, Russia), E-mail: Spirkin.andre@yandex.ru 

616.78:004.386 

10.21685/2307-5538-2019-4-8 

Background. The object of the study is the neural interfaces that control robotic 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 Mega 2560. 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. 

neurointerface, rhythms of brain activity, electroencephalogram, EEG pattern, artificial neural