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Recently, research and development of Brain-Computer Interface (BCI), which enables external device operation and communication, is performed actively by measuring brain activity and performing thought discrimination in real time. This system is expected as an alternative communication tool for patients with remarkably limited residual functions such as patients with severe quadriplegic paralysis due to spinal cord injury and patients with amyotrophic lateral sclerosis (ALS). Although BCI has expanded the area of its research, such as support from daily life and transfer assistance using a wheelchair, it is hard to say that BCI has been fully reduction to society. The reasons for this include falling responsiveness resulting from reflecting the user's intention in a complicated system and high cost by using large-scale equipment and expensive devices. By overcoming these technical issues and instability of the system, we can expect further acceleration of returning the BCI technology to society. In this research, we aim to develop a BCI system specialized for serial operation which does not require complicated functions in the system and controls a very small number of actuators. A drive module adopting a uniaxial motor for the actuator is prepared, and then the subject's emotion (attention, relaxation) is evaluated by electroencephalogram measurement and analysis. And the control accuracy of the motor at the time of executing the task using the emotion evaluation value as an input signal was evaluated.

Evaluation of Actuator Control Accuracy in BCI System using Simple Brain Wave Sensor