Chapter

Towards Practical Brain-Computer Interfaces

Part of the series Biological and Medical Physics, Biomedical Engineering pp 303-331

Date:

BCI Software Platforms

  • Clemens BrunnerAffiliated withInstitute for Knowledge Discovery, Graz University of TechnologySwartz Center for Computational Neuroscience, INC, UCSD Email author 
  • , Giuseppe AndreoniAffiliated withINDACO, Politecnico di Milano
  • , Lugi BianchiAffiliated withNeuroscience Department, Tor Vergata University of Rome
  • , Benjamin BlankertzAffiliated withMachine Learning Laboratory, Berlin Institute of Technology
  • , Christian BreitwieserAffiliated withInstitute for Knowledge Discovery, Graz University of Technology
  • , Shin’ichiro KanohAffiliated withDepartment of Electronics and Intelligent Systems, Tohoku Institute of Technology
  • , Christian A. KotheAffiliated withSwartz Center for Computational Neuroscience, INC, UCSD
  • , Anatole LécuyerAffiliated withNational Institute for Research in Computer Science and Control (INRIA)
  • , Scott MakeigAffiliated withSwartz Center for Computational Neuroscience, INC, UCSD
    • , Jürgen MellingerAffiliated withInstitute of Medical Psychology and Behavioral Neurobiology, University of Tübingen
    • , Paolo PeregoAffiliated withINDACO, Politecnico di Milano
    • , Yann RenardAffiliated withNational Institute for Research in Computer Science and Control (INRIA)
    • , Gerwin SchalkAffiliated withNew York State Department of Health, Wadsworth Center
    • , I Putu SusilaAffiliated withNuclear Equipment Engineering Center
    • , Bastian VenthurAffiliated withMachine Learning Laboratory, Berlin Institute of Technology
    • , Gernot R. Müller-PutzAffiliated withInstitute for Knowledge Discovery, Graz University of Technology

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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.