Performance Improvement of EEG-Based BCI Using Visual Feedback Based on Evaluation Scores Calculated by a Computer

Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:6086-6089. doi: 10.1109/EMBC46164.2021.9630801.

Abstract

In the study of an electroencephalography (EEG)-based brain computer interface (BCI) using the P300, there have been many reports on computer algorithms that identify the target intended by a user from multiple candidates. However, because the P300 amplitude depends on the subject's condition and is attenuated by physical and mental factors, such as fatigue and motivation, the performance of the BCI is low. Therefore, we aim to improve performance by introducing a feedback mechanism that provides the user with an evaluation calculated by the computer during EEG measurement. In this study, we conducted an experiment in which the user input one character from four characters on the display. By changing the character size according to the evaluation score calculated by the computer, the computer's current evaluation was fed back to the user. This is expected to change the consciousness of the user to enable them to execute a task by knowing the evaluation; that is, if the evaluation is high, the user needs to maintain the current state, and if the evaluation is low, a behavioral change, such as increasing attention, is required to improve the evaluation.As a result of comparing 10 subjects with and without feedback, accuracy improved for seven subjects that were given feedback.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Brain-Computer Interfaces*
  • Computers
  • Electroencephalography
  • Feedback, Sensory
  • Humans