User's Self-Prediction of Performance in Motor Imagery Brain-Computer Interface

Frontiers in Human Neuroscience
Minkyu AhnSung C Jun

Abstract

Performance variation is a critical issue in motor imagery brain-computer interface (MI-BCI), and various neurophysiological, psychological, and anatomical correlates have been reported in the literature. Although the main aim of such studies is to predict MI-BCI performance for the prescreening of poor performers, studies which focus on the user's sense of the motor imagery process and directly estimate MI-BCI performance through the user's self-prediction are lacking. In this study, we first test each user's self-prediction idea regarding motor imagery experimental datasets. Fifty-two subjects participated in a classical, two-class motor imagery experiment and were asked to evaluate their easiness with motor imagery and to predict their own MI-BCI performance. During the motor imagery experiment, an electroencephalogram (EEG) was recorded; however, no feedback on motor imagery was given to subjects. From EEG recordings, the offline classification accuracy was estimated and compared with several questionnaire scores of subjects, as well as with each subject's self-prediction of MI-BCI performance. The subjects' performance predictions during motor imagery task showed a high positive correlation (r= 0.64,p< 0.01). Interestingly...Continue Reading

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Citations

Feb 13, 2020·Sensors·Malik M Naeem MannanMyung Yung Jeong
Sep 10, 2020·Frontiers in Human Neuroscience·Minji LeeSeong-Whan Lee
Feb 25, 2020·Journal of Healthcare Engineering·Hyeonseok KimYasuharu Koike
Feb 8, 2019·Frontiers in Human Neuroscience·Sébastien RimbertStéphanie Fleck
Dec 18, 2020·Frontiers in Neuroscience·Cecilia Lindig-LeónLaurent Bougrain
Apr 13, 2021·Frontiers in Neuroscience·Xiongliang Xiao, Yuee Fang
Apr 24, 2021·Frontiers in Human Neuroscience·Nikki LeeuwisMaryam Alimardani
Aug 6, 2021·Frontiers in Human Neuroscience·Sanghum WooMinkyu Ahn

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Software Mentioned

BCI2000
CSP
Fisher Linear Discriminant Analysis ( FLDA )
Biosemi Active 2
FLDA
MATLAB

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