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We introduce a user-friendly steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) system. Single-channel EEG is recorded using a low-noise dry electrode. Compared to traditional gel-based multi-sensor EEG systems, a dry sensor proves to be more convenient, comfortable and cost effective. A hardware system was built that displays(More)
This paper presents a new intensity-based stereo algorithm using cooperative bi-directional matching with a hierarchical multilevel structure. Based on a new model of piecewise smooth depth elds and the consistency constraint, the algorithm is able to estimate the 3-D structure and detect its discontinuities and the occlusion reliably with low computational(More)
The timing of a behavioral response, such as a button press in reaction to a visual stimulus, is highly variable across trials. In this paper we describe a methodology for single-trial analysis of electroencephalography (EEG) which can be used to reduce the error in the estimation of the timing of the behavioral response and thus reduce the error in(More)
Most visual stimuli we experience on a day-to-day basis are continuous sequences, with spatial structure highly correlated in time. During rapid serial visual presentation (RSVP), this correlation is absent. Here we study how subjects' target detection responses, both behavioral and electrophysiological, differ between continuous serial visual sequences(More)
It is well-known that the problem of MEG source localization can be cast as an optimization problem. So far, there have been many works in which various optimization methods were adopted for source localization. In this paper, we compare the performance of three typical and widely used optimization techniques for a specific MEG source localization problem.(More)
We describe a spatio-temporal linear discriminator for single-trial classification of multi-channel electroencephalography (EEG). No prior information about the characteristics of the neural activity is required, i.e., the algorithm requires no knowledge about the timing and spatial distribution of the evoked responses. The algorithm finds a temporal(More)