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A motor imagery based brain-computer interface (BCI) translates the subject's motor intention into a control signal through real-time detection of characteristic EEG spatial distributions corresponding to motor imagination of different body parts. In this paper, we implemented a three-class BCI manipulated through imagination of left hand, right hand and foot movements, inducing different spatial...
In brain-machine interface (BMI) applications, neural firing activities have been represented by spike counts with a fixed-width time bin. Adaptive models have been designed to utilize these bin counts for mapping the associated behavior which is typically 2D or 3D hand movement. However, the representation of the firing activities can be enriched by binning neural spikes with multiple time scales...
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