Neural Network for Recognition of Brain Wave Signals

Karam, Jalal, Al-Majeed, Salah ORCID: 0000-0002-5932-9658, Yalung, Christofer and Mirtskhulava, Lela (2016) Neural Network for Recognition of Brain Wave Signals. International Journal of Enhanced Research in Science, Technology and Engineering, 5 (10). pp. 36-42.

Text (Published version) 5998 Al-Majeed (2016) Neural Network.pdf - Published Version Restricted to Repository staff only until 1 January 2099. (Other reason). Available under License All Rights Reserved. Download (386kB)

Abstract

Improving life quality for disabled patients and overall improvement of human thought concentration especially individuals suffering from Autism and Alzheimer can be accomplished with the aid of Brainwave Computer Interface (BCI). In this paper, a Radial Basis Functions (RBF) Artificial Neural Network (ANN) is constructed and a BCI is implemented using NeuroSkyS EEG biosensor for the recognition of brain signals. The analysis is presented through the consideration of a noisy environment to simulate a BCI in real world applications. A total of 256 data points are acquired in each thought. The data are transmitted via Bluetooth for MATLAB documentation and recognition rates in the highest 70 percent are recorded.

Item Type:	Article
Article Type:	Article
Additional Information:	The final published article is freely available from the publishers website see URL above.
Uncontrolled Keywords:	Neural Network; BCI; NeuroSky; Feature Extraction; Noisy environment
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas:	Applied Business & Technology
Depositing User:	Susan Turner
Date Deposited:	21 Sep 2018 09:03
Last Modified:	13 Mar 2024 12:59
URI:	https://eprints.glos.ac.uk/id/eprint/5998

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