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Towards Practical Brain-Computer Interfaces pp 303–331Cite as

BCI Software Platforms

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Part of the book series: Biological and Medical Physics, Biomedical Engineering ((BIOMEDICAL))

Abstract

In this chapter, we provide an overview of publicly available software platforms for brain–computer interfaces. We have identified seven major BCI platforms and one platform specifically targeted towards feedback and stimulus presentation. We describe the intended target user group (which includes researchers, programmers, and end users), the most important features of each platform such as availability on different operating systems, licences, programming languages involved, supported devices, and so on. These seven platforms are: (1) BCI2000, (2) OpenViBE, (3) TOBI Common Implementation Platform (CIP), (4) BCILAB, (5) BCI++, (6) xBCI, and (7) BF++. The feedback framework is called Pyff. Our conclusion discusses possible synergies and future developments, such as combining different components of different platforms. With this overview, we hope to identify the strengths and weaknesses of each available platform, which should help anyone in the BCI research field in their decision which platform to use for their specific purposes.

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Notes

  1. 1.

    www.gnu.org/licenses/gpl.html

  2. 2.

    www.bci2000.org

  3. 3.

    doc.bci2000.org

  4. 4.

    bbs.bci2000.org

  5. 5.

    bci2000.org/downloads/BCPy2000

  6. 6.

    gcc.gnu.org

  7. 7.

    www.mingw.org

  8. 8.

    openvibe.inria.fr

  9. 9.

    www.gnu.org/copyleft/lesser.html

  10. 10.

    www.gtk.org

  11. 11.

    sourceforge.net/apps/wordpress/itpp

  12. 12.

    www.cs.unc.edu/Research/vrpn

  13. 13.

    openvibe.inria.fr/documentation/latest

  14. 14.

    www.tobi-project.org/download

  15. 15.

    http://arxiv.org/abs/1103.4717v1

  16. 16.

    www.tobi-project.org/download

  17. 17.

    bci.tugraz.at/downloads

  18. 18.

    www.boost.org

  19. 19.

    www.libsdl.org

  20. 20.

    sccn.ucsd.edu/wiki/BCILAB

  21. 21.

    opensoundcontrol.org

  22. 22.

    sccn.ucsd.edu

  23. 23.

    www.sensibilab.campuspoint.polimi.it

  24. 24.

    www.wxwidgets.org

  25. 25.

    irrlicht.sourceforge.net

  26. 26.

    www.hitl.washington.edu/artoolkit

  27. 27.

    xbci.sourceforge.net

  28. 28.

    www.brainterface.com

  29. 29.

    bbci.de/pyff

  30. 30.

    www.json.org

  31. 31.

    www.pygame.org

  32. 32.

    www.python.org

  33. 33.

    www.riverbankcomputing.co.uk/software/pyqt/intro

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Acknowledgements

The views and the conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the corresponding funding agencies. The authors would like to acknowledge the following projects and funding sources:

BCI2000: This work was supported by grants from the US Army Research Office (W911NF-07-1-0415, W911NF-08-1-0216) and the NIH/NIBIB (EB006356 and EB000856).

OpenViBE: This work was partly supported by grants of the French National Research Agency under the OpenViBE (ANR-05-RNTL-016) and OpenViBE2 (ANR-09-CORD-017) projects.

TOBI: This work is supported by the European ICT Programme Project FP7-224631.

BCILAB: Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-10-2-0022. Initial development was supported by a gift from the Swartz Foundation (Oldfield, NY) and a basic research grant of the Office of Naval Research (ONR).

Pyff: This work was partly supported by grants of the Bundesministerium für Bildung und Forschung (BMBF) (FKZ 01IB001A, 01GQ0850) and by the FP7-ICT Programme of the European Community, under the PASCAL2 Network of Excellence, ICT-216886.

Author information

Authors and Affiliations

  1. Institute for Knowledge Discovery, Graz University of Technology, Graz, Austria

    Clemens Brunner, Christian Breitwieser & Gernot R. Müller-Putz

  2. Swartz Center for Computational Neuroscience, INC, UCSD, San Diego, CA, USA

    Clemens Brunner, Christian A. Kothe & Scott Makeig

  3. INDACO, Politecnico di Milano, Milan, Italy

    Giuseppe Andreoni & Paolo Perego

  4. Neuroscience Department, Tor Vergata University of Rome, Rome, Italy

    Lugi Bianchi

  5. Machine Learning Laboratory, Berlin Institute of Technology, Berlin, Germany

    Benjamin Blankertz & Bastian Venthur

  6. Department of Electronics and Intelligent Systems, Tohoku Institute of Technology, Sendai, Japan

    Shin’ichiro Kanoh

  7. Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany

    Jürgen Mellinger

  8. National Institute for Research in Computer Science and Control (INRIA), Rennes, France

    Anatole Lécuyer & Yann Renard

  9. New York State Department of Health, Wadsworth Center, Albany, NY, USA

    Gerwin Schalk

  10. Nuclear Equipment Engineering Center, Tangerang Selatan, Indonesia

    I Putu Susila

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  1. Clemens Brunner
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Correspondence to Clemens Brunner .

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  1. Baltimore Drive 5700Apt 167, La Mesa, 91942, California, USA

    Brendan Z. Allison

  2. Starlab Neuroscience Research, Teodor Roviralta 45, Barcelona, 08022, Spain

    Stephen Dunne

  3. , School of Engineering, Swiss Federal Institute of Technology, EPFL STI-CNBI, ELB 141, Station 11, Lausanne, 1015, Switzerland

    Robert Leeb

  4. , School of Engineering, Swiss Federal Institute of Technology, EPFL STI-CNBI, ELB 138. Station 11, Lausanne, 1015, Switzerland

    José Del R. Millán

  5. , Faculty EEMCS, University of Twente, Enschede, 7500, Netherlands

    Anton Nijholt

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Brunner, C. et al. (2012). BCI Software Platforms. In: Allison, B., Dunne, S., Leeb, R., Del R. Millán, J., Nijholt, A. (eds) Towards Practical Brain-Computer Interfaces. Biological and Medical Physics, Biomedical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29746-5_16

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