Method of Electroencephalography Electrode Selection for Motor Imagery Application

Abstract

Brain-computer interface (BCI) technology is commonly used to describe the brain signal activity non-invasively. The development of EEG devices which is used to record brain activity continues to be carried out, both in terms of accuracy, suitability, computation, and cost. However, the complexity arises with increased electrode numbers. In some studies, minimizing the number of electrodes can be a solution to reduce computational time, cost, and the shape of the EEG device, without compromising the level of accuracy. By choosing particular electrodes which are highly related to the activity, the electrode usage can be reduced. This study used correlation coefficient method which is proposed to determine the best electrode pairs. Moreover, the electrodes which have similar features is eliminated. Based on the experimental and test results, it showed that the results were very good, where the average accuracy and F1 Score was increasing by 2% and 4% compared to the use of all electrodes, this increasing was followed by a decreasing in computation time with an average decreasing in debugging time by 35%.