DEVELOPING A BRAIN COMPUTER INTERFACE CONTROL SYSTEM FOR ROBOTIC MOVEMENT IN TWO DIMENSIONS

1 online resource (64 pages) : PDF

2014

University of North Carolina at Charlotte

This paper concerns the theory behind developing a brain computer interface (BCI) and the applications of such a system. Signal acquisition methods such as Functional Magnetic Resonance Imaging (fMRI), Near-Infrared Spectroscopy (NIRS), Magnetoencephalography (MEG), Electrocorticography (ECoG), and Electroencephalography (EEG) are discussed. There is also a review of the different types of Event Related Potentials (ERP) and signal extraction methods for generating filters from the captured data to generate a model for a BCI. Finally, this paper covers a review of notable BCIs that are being utilized in a wide range of applications and gives a working example using BCILAB to generate results from a sample data set using the techniques discussed in the paper.

masters theses

Electrical engineering

M.S.

BCI
Brain Computer Interface
EEG

Electrical Engineering

Conrad, James

Kuyath, Stephen
Kakad, Yogendra

Thesis (M.S.)--University of North Carolina at Charlotte, 2014.

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Major_uncc_0694N_10725

http://hdl.handle.net/20.500.13093/etd:1473