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Generating Ten BCI Commands Using Four Simple Motor Imageries
A maximum of ten different BCI commands can be generated by using four motor imageries in pairs. This study aims to achieve high classification performances for BCI commands produced from four motor imageries by implementing a small-sized deep neural network (DNN). The presented method is evaluated on the four-class datasets of BCI Competitions III and IV, and an average classification performance of 81. 8% is achieved for ten classes.
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