Do not Move! Entropy Driven Detection of Intentional Non-control During Online SMR-BCI Operations
Correct classification of motor imagery tasks is not the only requirement of a Brain-Computer Interface (BCI) based on Sensorimotor Rhythms (SMR). Indeed, a SMR-BCI controlling an external device (e.g., robotic prostheses) needs to reliably detect even if the user is in the so-called Intentional Non-Control (INC) state. In this work, we propose a novel approach to online detect INC and thus, to reduce undesired delivered commands during SMR-BCI operations. Results with six healthy subjects show that the proposed INC detection framework does not affect the online BCI performance and, more importantly, it reduces the number of unintentionally delivered BCI commands with respect to a traditional approach (in average 42.7 ± 13.76 % less).
KeywordsMotor Imagery Canonical Variate Analysis Quadratic Discriminate Analysis Common Spatial Pattern Detection Framework
We thank g.Tec Medical Engineering Company for hardware support.
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