Abstract
The goal of this work is to design a BCI that can then be used to control a serious game for concentration training. A 32-Electrode cap system was used, in addition to a bandpass and notch filter, t-SNE dimension reduction, standard deviation outlier detection as well as a SVM classifier. A maximum classification accuracy of 80% was achieved when using a four class classification system. Our BCI-Controlled Serious Game is viable and we thus plan to evaluate our application in a pilot test.
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Garcia-Agundez, A., Dobermann, E., Göbel, S. (2018). Design of a BCI Controlled Serious Game for Concentration Training. In: Göbel, S., et al. Serious Games. JCSG 2018. Lecture Notes in Computer Science(), vol 11243. Springer, Cham. https://doi.org/10.1007/978-3-030-02762-9_17
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