컨볼루션 신경망 기반 운동심상을 이용한 뇌의 연결성 분석 및 분류방법

초록

The brain-computer interface (BCI) is a technology that predicts user’s intention through artificial intelligent algorithm and control robot or computer accordingly and is recognized as a core technology for the future by various organizations around the world. BCI is used in various applications according to the implementation method (Slow Cortical Potentials, Sensorimotor Rhythms, P300, Steady State Visually Evoked Potential, Directional Tuning, etc). However, to use BCI in real life, it is necessary to turn on/off the system according to the situation or to change the system mode (typing, robot control, electric wheelchair control, etc). In this paper, we developed an algorithm to measure various states (resting, speech imagery, legs-motor imagery, hands-motor imagery) of subjects by measuring and analyzing EEG in 10 subjects and as a result, we were able to distinguish the state with an accuracy of 88.25%. We expected that BCI technology would be put into practical use as a critical algorithm for changing BCI mode.

키워드