Elstob, Daniel and Secco, Emanuele Lindo (2016) A LOW COST EEG BASED BCI PROSTHETIC USING MOTOR IMAGERY. International Journal of Information Technology Convergence and Services (IJITCS), 6 (1). pp. 23-36.


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Brain Computer Interfaces (BCI) provide the opportunity to control external devices using the brain
ElectroEncephaloGram (EEG) signals. In this paper we propose two software framework in order to
control a 5 degree of freedom robotic and prosthetic hand. Results are presented where an Emotiv
Cognitive Suite (i.e. the 1st framework) combined with an embedded software system (i.e. an open source
Arduino board) is able to control the hand through character input associated with the taught actions of
the suite. This system provides evidence of the feasibility of brain signals being a viable approach to
controlling the chosen prosthetic. Results are then presented in the second framework. This latter one
allowed for the training and classification of EEG signals for motor imagery tasks. When analysing the
system, clear visual representations of the performance and accuracy are presented in the results using a
confusion matrix, accuracy measurement and a feedback bar signifying signal strength. Experiments with
various acquisition datasets were carried out and with a critical evaluation of the results given. Finally
depending on the classification of the brain signal a Python script outputs the driving command to the
Arduino to control the prosthetic. The proposed architecture performs overall good results for the design
and implementation of economically convenient BCI and prosthesis.

Item Type: Article
Additional Information and Comments: First published in Journal of Information Technology Convergence and Services. AIRCC Publishing.
Faculty / Department: Faculty of Science > Mathematics and Computer Science
Depositing User: Emanuele Secco
Date Deposited: 27 May 2016 15:12
Last Modified: 08 Dec 2017 12:55
URI: https://hira.hope.ac.uk/id/eprint/1224

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