Brain-Computer Interfaces (BCIs) are communication systems, which enable users to send commands to computers by using brain activity only; this activity being generally measured by Electroencephalography (EEG). BCIs are generally designed according to a pattern recognition approach, i.e., by extracting features from EEG signals, and by using a classifier to identify the user’s mental state from...

In this study, a novel control algorithm, based on a P300-based brain-computer interface (BCI) is fully developed to control a 2-DoF robotic arm. Eight subjects including 5 men and 3 women perform a 2-dimensional target tracking in a simulated environment. Their EEG (Electroencephalography) signals from visual cortex are recorded and P300 components are extracted and evaluated to perform a real...

Hansang Cho a, Brian Lee a, Gang L. Liu b, Ajay Agarwal c and Luke P. Lee *a aBiomolecular Nanotechnology Center, Berkeley Sensor & Actuator Center, Department of Bioengineering, University of California, Berkeley, California 94720, USA. E-mail: [email protected]; Fax: +1 510 642 5835; Tel: +1 510 642 5855 bDepartment of Electrical and Computer Engineering, University of Illinois at Urbana-Cha...

Brian Dellabetta,1,2 Taylor L. Hughes,3 Matthew J. Gilbert,1,2 and Benjamin L. Lev4 1Department of Electrical and Computer Engineering, University of Illinois, Urbana, Illinois 61801, USA 2Micro and Nanotechnology Laboratory, University of Illinois, Urbana, Illinois 61801, USA 3Department of Physics, University of Illinois, Urbana, Illinois 61801, USA 4Departments of Applied Physics and Physics...

Juan G. Restrepo, 2, ∗ Edward Ott, 3 and Brian R. Hunt 4 1 Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742, USA 2 Department of Mathematics, University of Maryland, College Park, Maryland 20742, USA 3 Department of Physics and Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742, U...