Practical Noninvasive Brain–Machine Interface System for Communication and Control

The brain–machine interface (BMI) or brain–computer interface (BCI) is an interface technology that utilizes neurophysiological signals from the brain to control external machines or computers. We have developed electroencephalography (EEG)-based BMI systems to help persons with physical disabilities. We first applied the P300 paradigm for environmental control and communication. We attempted to optimize the visual stimuli for our P300-BMI and prepared a green/blue flicker matrix. We showed that the new matrix was associated with a better subjective feeling of comfort than was the conventional white/gray flicker matrix and that the new matrix was associated with better performance. We further proposed an advanced system by adding augmented reality (AR) in which an agent robot was applied as a moving remote controller.

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