PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Biased Feedback in Brain-Computer Interfaces
Alvaro Barbero and Moritz Grosse-Wentrup
Journal of NeuroEngineering and Rehabilitation Volume 7, Number 34, pp. 1-4, 2010.

Abstract

Even though feedback is considered to play an important role in learning how to operate a brain-computer interface (BCI), to date no significant influence of feedback design on BCI-performance has been reported in literature. In this work, we adapt a standard motor-imagery BCI-paradigm to study how BCI-performance is affected by biasing the belief subjects have on their level of control over the BCI system. Our findings indicate that subjects already capable of operating a BCI are impeded by inaccurate feedback, while subjects normally performing on or close to chance level may actually benefit from an incorrect belief on their performance level. Our results imply that optimal feedback design in BCIs should take into account a subject's current skill level.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
ID Code:7003
Deposited By:Moritz Grosse-Wentrup
Deposited On:18 September 2010