Advertisement

Hybrid EEG-Based BCI User Interface for Action Selection

  • J. Pascual
  • R. Lorenz
  • B. Blankertz
  • C. Vidaurre
Part of the Biosystems & Biorobotics book series (BIOSYSROB, volume 1)

Abstract

In this study we developed a Graphical User Interface (GUI) to control a Brain-Computer Interface (BCI) by means of Event Related Potentials (ERP) and/or Motor Imagery (MI). It allows users to select actions to operate an upper-limb neuroprosthesis. The action’s selection is divided into 2 steps: choice and confirmation, which can be controlled using ERP or MI. We also present results of experiments with 12 participants who used this GUI and show that high performance is achieved with all possible combinations of paradigms. The GUI mode in which both the selection and confirmation steps use the ERP paradigm obtains the highest accuracy.

Keywords

Graphical User Interface Motor Imagery Event Relate Poten Action Selection Functional Electrical Stimulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Pfurtscheller, G., Müller-Putz, G., Pfurtscheller, J., Rupp, R.: EEG-based asynchronous BCI controls functional electrical stimulation in a tetraplegic patient. EURASIP Journal on Applied Signal Processing, 3152–3155 (2005)Google Scholar
  2. 2.
    Tavella, M., Leeb, R., Rupp, R., del R. Millán, J.: Natural Non-Invasive Hand Neuroprosthesis. International Journal of Bioelectromagnetism 13 (2011)Google Scholar
  3. 3.
    Pascual, J., Velasco-Álvarez, F., Müller, K.-R., Vidaurre, C.: First study towards linear control of an upper-limb neuroprosthesis with an EEG-based brain-computer interfaceGoogle Scholar
  4. 4.
    Yuksel, B.F., Donnerer, M., Tompkin, J., Steed, A.: Novel P300 BCI Interfaces to Directly Select Physical and Virtual ObjectsGoogle Scholar
  5. 5.
    Blankertz, B., Dornhege, G., Krauledat, M., Schröder, M., Williamson, J., Murray-Smith, R., Müller, K.-R.: The Berlin Brain-Computer Interface Presents the Novel Typewriter Hex-O-SpellGoogle Scholar
  6. 6.
    Acqualagna, L., Blankertz, B.: A gaze independent speller based on rapid serial visual presentation. In: Conf. Proc. IEEE Eng. Med. Biol. Soc., p. 45603 (2011)Google Scholar
  7. 7.
    Blankertz, B., Lemm, S., Treder, M., Haufe, S., Müller, K.-R.: Single-trial analysis and classification of ERP components - a tutorial. NeuroImage 56, 814–825 (2010)CrossRefGoogle Scholar
  8. 8.
    Blankertz, B., Tomioka, R., Lemm, S., Kawanabe, M., Müller, K.-R.: Optimizing spatial filters for robust EEG single-trial analysis. IEEE Signal Process. Mag. 25(1), 41–56 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • J. Pascual
    • 1
  • R. Lorenz
    • 2
  • B. Blankertz
    • 2
  • C. Vidaurre
    • 1
  1. 1.Machine Learning Group, Computer Science FacultyBerlin Institute of TechnologyBerlinGermany
  2. 2.Neurotechnology GroupBerlin Institute of TechnologyBerlinGermany

Personalised recommendations