Fuzzy adaptive neurofeedback training: An efficient neurofeedback training procedure providing a more accurate progress rate for trainee

In this paper, a new fuzzy adaptive neurofeedback training procedure (FNFT) is proposed, in which a more effective performance in neurofeedback training can be expected. In the proposed FNFT, the threshold is adaptively set considering the cortical activity of the subject. Scoring index (SI) (the number of points increased in subject's score) is set according to the brain activity of the subject and is calculated using a fuzzy rule based system. When training feature surpasses the threshold, the SI points are then added to the points of the subject. This adaptive scoring index leads to having an efficient indicator for the success rate of the subject. In addition, the subject is rewarded with an audio or visual feedback. The sound intensity of the audio feedback and the length and width of the video frame are adjusted in accordance with the SI. Finally, an EEG feature is also considered (brain mental fatigue index) to stop the training as the subject becomes mentally fatigued.