Development of an ECoG Controlled Electric Wheelchair for Assisting paralyzed people.

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This research aims at developing an ECoG-based Brain Machine Interface(BMI) assist device. As results, we have developed the electric wheelchair that is controlled with human ECoG(Electro-Corti-Graphic) signals : the control algorithm consists of human intention classification(i. e., 4 motions-going forward, going backward, turning left, turning right) and razor-range-finder based autonomous obstacle avoidance. We have also developed the 300 speller system that point out objects in 3D space, and developed a robotic hand and arm. With those combinations, we have constructed an upper-limb assist device.