Prediction of motor imagery based brain computer interface performance using a reaction time test

Author

Sam Darvishi;Derek Abbott;Mathias Baumert

Author_Institution

Centre for Biomedical Engineering, School of Electrical and Electronic Engineering, The University of Adelaide, SA 5005, Australia

fYear

2015

Firstpage

2880

Lastpage

2883

Abstract

Brain computer interfaces (BCIs) enable human brains to interact directly with machines. Motor imagery based BCI (MI-BCI) encodes the motor intentions of human agents and provides feedback accordingly. However, 15-30% of people are not able to perform vivid motor imagery. To save time and monetary resources, a number of predictors have been proposed to screen for users with low BCI aptitude. While the proposed predictors provide some level of correlation with MI-BCI performance, simple, objective and accurate predictors are currently not available. Thus, in this study we have examined the utility of a simple reaction time (SRT) test for predicting MI-BCI performance. We enrolled 10 subjects and measured their motor imagery performance with either visual or proprioceptive feedback. Their reaction time was also measured using a SRT test. The results show a significant negative correlation (r ≈ -0.67) between SRT and MI-BCI performance. Therefore SRT may be used as a simple and reliable predictor of MI-BCI performance.

Keywords

"Visualization","Accuracy","Correlation","Electroencephalography","Atmospheric measurements","Particle measurements","Brain-computer interfaces"

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE

ISSN

1094-687X

Electronic_ISBN

1558-4615

Type

conf

DOI

10.1109/EMBC.2015.7318993

Filename

7318993