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Unsupervised Online Calibration of a c-VEP Brain-Computer Interface (BCI)

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 8131)

Abstract

Brain-Computer Interfaces (BCIs) can be used to give paralyzed patients a means for communication. But so far, only supervised methods have been used for calibration of an online BCI. In this paper we present a method that allows to calibrate a BCI online and unsupervised. Based on offline data we show that the unsupervised calibration method works and validate the results in an online experiment with 8 subjects, who were able to control the BCI with an average accuracy of 85 %. We thereby have shown for the first time that an online unsupervised calibration of a BCI is possible and allows for successful BCI control.

Keywords

  • Brain-Computer interface (BCI)
  • unsupervised learning

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Spüler, M., Rosenstiel, W., Bogdan, M. (2013). Unsupervised Online Calibration of a c-VEP Brain-Computer Interface (BCI). In: Mladenov, V., Koprinkova-Hristova, P., Palm, G., Villa, A.E.P., Appollini, B., Kasabov, N. (eds) Artificial Neural Networks and Machine Learning – ICANN 2013. ICANN 2013. Lecture Notes in Computer Science, vol 8131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40728-4_28

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  • DOI: https://doi.org/10.1007/978-3-642-40728-4_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40727-7

  • Online ISBN: 978-3-642-40728-4

  • eBook Packages: Computer ScienceComputer Science (R0)