NDLI: Proposal of a Brain Computer Interface to command an autonomous car

Content Provider	IEEE Xplore Digital Library
Author	Castillo, J. Muller, S. Caicedo, E. Ferreira de Souza, A. Bastos, T.
Copyright Year	2014
Description	Author affiliation: Post-Grad. Program of Electr. Eng., Univ. of Valle, Cali, Colombia (Caicedo, E.) \|\| Post-Grad. Program of Electr. Eng., Fed. Univ. of Espirito Santo, Vitoria, Brazil (Castillo, J.; Muller, S.; Bastos, T.) \|\| Post-Grad. Program of Inf., Fed. Univ. of Espirito Santo, Vitoria, Brazil (Ferreira de Souza, A.)
Abstract	This paper presents a proposal of Brain Computer Interface (BCI) to command an autonomous car. This BCI is based on the paradigm of visual evoked potentials (VEP) and event-related desynchronization (ERD). A menu interface is presented to the user with disabilities in order he/she can choose a destination for the autonomous car. The selection of the final destination is performed using visual stimuli flickering at different frequencies, analyzed through the analysis of brain signals present at the occipital region of the user's scalp. The power spectrum of these signals is then obtained, in order to get the frequency of the visual stimulation. Preliminary tests were performed with healthy users and people with disabilities, which reached an average success rate above 90%. The proposed system is also capable of turning on/off the stimuli, thus reducing the fatigue associated with particular visual stimuli.
Starting Page	1
Ending Page	6
File Size	792920
Page Count	6
File Format	PDF
ISSN	23267844
e-ISBN	9781479956890
DOI	10.1109/BRC.2014.6880969
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-26
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Autonomous Car Visualization Navigation Brain Computer Interface ERD Educational institutions SSVEP Brain-computer interfaces Mobile robots Proposals Equations
Content Type	Text
Resource Type	Article

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