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simBCI is a framework for generating artificial EEG data and to test BCI classification methods. The combination allows the study of EEG models and BCI signal processing methods together in controllable conditions as each tested configuration features only what was specified. It is intended for offline analysis of BCI models and methods and to provide intuition about the behavior of such techniques. Ultimately, human experiments are necessary to validate the ideas arising from the use of the framework.
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The potentially useful results produced by simBCI are classification accuracies obtained in different conditions, and elementary visualizations of the data after different transformations. Although in principle it would be possible to extract models generated in simBCI and apply them online, or run simBCI on real data, these have not so far been design goals.
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The potentially useful results produced by simBCI are classification accuracies obtained in different conditions, and elementary visualizations of the data after different transformations. Although in principle it would be possible to extract models generated with simBCI and apply them online, or to run simBCI on real data, these have not been the design goals so far.
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The target audience of simBCI are advanced students, researchers, teachers and engineers interested in obtaining a deeper understanding of the operation of BCI models and signal processing techniques.
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If you use simBCI in your academic work, please cite the following short conference abstract in your publication,
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*J.T. Lindgren, A. Merlini, A. Lécuyer and F.P. Andriulli. SimBCI - Tool to simulate EEG and BCI. BCI Meeting, Asilomar/CA, 2018.* (accepted)
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*J.T. Lindgren, A. Merlini, A. Lécuyer and F.P. Andriulli. SimBCI - Tool to simulate EEG and BCI. The 7th International BCI Meeting, Asilomar/CA, 2018.* (accepted)
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We will provide a reference to the journal paper after it has been accepted for publication.
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