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Brain-computer interfaces based on event-related potentials face a trade-off between the speed and accuracy of the system, as both depend on the number of iterations. Increasing the number of iterations leads to a higher accuracy but reduces the speed of the system. This trade-off is generally dealt with by finding a fixed number of iterations that give a(More)
P300-based Brain Computer Interfaces offer communication pathways which are independent of muscle activity. Mostly visual stimuli, e.g. blinking of different letters are used as a paradigm of interaction. Neural degenerative diseases like amyotrophic lateral sclerosis (ALS) also cause a decrease in sight, but the ability of hearing is usually unaffected.(More)
INTRODUCTION In the field of Brain-Computer Interfaces (BCI), the original two-class oddball paradigm has been extended to multiple stimuli with balanced probabilities and random presentation sequences. Exploiting the differences between standard and deviant ERP responses, these multi-class paradigms are suitable for communication and control. METHODS The(More)
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