title: High theta and low alpha powers may be indicative of BCI-illiteracy in motor imagery.
abstract: In most brain computer interface (BCI) systems, some target users have significant difficulty in using BCI systems. Such target users are called 'BCI-illiterate'. This phenomenon has been poorly investigated, and a clear understanding of the BCI-illiteracy mechanism or a solution to this problem has not been reported to date. In this study, we sought to demonstrate the neurophysiological differences between two groups (literate, illiterate) with a total of 52 subjects. We investigated recordings under non-task related state (NTS) which is collected during subject is relaxed with eyes open. We found that high theta and low alpha waves were noticeable in the BCI-illiterate relative to the BCI-literate people. Furthermore, these high theta and low alpha wave patterns were preserved across different mental states, such as NTS, resting before motor imagery (MI), and MI states, even though the spatial distribution of both BCI-illiterate and BCI-literate groups did not differ. From these findings, an effective strategy for pre-screening subjects for BCI illiteracy has been determined, and a performance factor that reflects potential user performance has been proposed using a simple combination of band powers. Our proposed performance factor gave an r = 0.59 (r(2) = 0.34) in a correlation analysis with BCI performance and yielded as much as r = 0.70 (r(2) = 0.50) when seven outliers were rejected during the evaluation of whole data (N = 61), including BCI competition datasets (N = 9). These findings may be directly applicable to online BCI systems.
authors.affiliation: School of Information and Communications, Gwangju Institute of Science and Technology, Gwangju, South Korea.
authors.forename: Minkyu
authors.initials: M
authors.lastname: Ahn
authors.forename: Hohyun
authors.initials: H
authors.lastname: Cho
authors.forename: Sangtae
authors.initials: S
authors.lastname: Ahn
authors.forename: Sung Chan
authors.initials: SC
authors.lastname: Jun
mesh_terms: D000328:Adult; D000513:Alpha Rhythm / Q000502:physiology*; D062207:Brain-Computer Interfaces; D016002:Discriminant Analysis; D004522:Educational Status; D005260:Female; D006801:Humans; D019359:Knowledge; D008297:Male; D012146:Rest / Q000502:physiology; D013826:Theta Rhythm / Q000502:physiology*