Generation of Electroencephalography Recognition Patterns via Genetic Algorithm

Electroencephalogram‐based control of a mobile robot

“…The authors have reported on the effectiveness of an analytical method that focuses on the correlation coefficient between electrodes in the time domain when the eyes are closed and have proposed a correlation pattern matching (CPM) method using a mutual correlation coefficient [12,13]. However, because of the noise generated by blinking and eyeball movement when the eyes are open, a dramatic deterioration in accuracy rate is shown in this section.…”

“…In Section 4, the authors propose an analytical method that is robust in the face of such noise. Note that in the authors' past research [12][13][14], because the individual differences in brain waves were so significant, the authors recommended creating recognition patterns for each individual. In this research as well, the authors create recognition patterns for each individual.…”

“…The authors proposed a direction recognition system [12][13][14] using brain waves for pattern matching emphasizing the correlation coefficient between electrodes, and achieved roughly 70% accuracy rate for discriminating left and right when the eyes were closed. However, in the system the accuracy rate dropped when the eyes were opened due to the noise of eyeball movement and blinking, and so the system was considered insufficient for practical applications.…”