Abstract
The contribution of the brain-computer interface (BCI) ranges from prevention of disease to neuronal control for disabled peoples. BCI-controlled virtual reality system is a potentially important new assistive technology area to aid various physically disable people (i.e., paralyzed people) by monitoring brain activity and translating desired signal features to operate external devices. This research used motor imagery achieved from EEG data implicating three main phases (i.e., preprocessing, features extraction, and classification of brain signals). This research used linear discriminant analysis (LDA) classifier to achieve decision boundary between left hand and right hand imagination. In this context, motor imagery-based EEG data was segmented and classified to be used as a controller for BCI. Experimental results reflect the significant impact of various classifiers and is expected to aid paralyzed people in converting their imagination into reality.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
