Prediction of motor imagery based brain computer interface performance using a reaction time test | IEEE Conference Publication | IEEE Xplore

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


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...Show More

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.
Date of Conference: 25-29 August 2015
Date Added to IEEE Xplore: 05 November 2015
ISBN Information:

ISSN Information:

PubMed ID: 26736893
Conference Location: Milan, Italy

References

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