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Toward Non-invasive BCI-Based Movement Decoding

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Neuroprosthetics and Brain-Computer Interfaces in Spinal Cord Injury

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Abstract

Although motor imagery was used for the first BCI-controlled neuroprosthetic applications, it has turned out that it is a limited experimental strategy when it comes to control of more than two degrees of freedom. More natural ways for controlling the hand and ultimately the whole arm function have been identified in using attempted movement and even the attempt to move the whole arm. First evidence on the feasibility of these new BCI principles for neuroprosthesis control is discussed in this chapter.

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Acknowledgments

This is to acknowledge Andreea I. Sburlea, Reinmar J. Kobler, Joana Pereira, Catarina Lopes-Dias, Lea Hehenberger, and Valeria Mondini who all contributed to this chapter.

This work was partly supported by the EU-Project MoreGrasp (643955) and the ERC-Cog-2015 “Feel Your Reach” (681231).

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Authors and Affiliations

  1. Institute of Neural Engineering, BCI Lab, Graz University of Technology, Graz, Austria

    Gernot Müller-Putz

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  1. Gernot Müller-Putz
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Correspondence to Gernot Müller-Putz .

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Editors and Affiliations

  1. Institute of Neural Engineering, BCI Lab, Graz University of Technology, Graz, Austria

    Gernot Müller-Putz

  2. Heidelberg University Hospital – Spinal Cord Injury Center, Heidelberg, Germany

    Rüdiger Rupp

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Müller-Putz, G. (2021). Toward Non-invasive BCI-Based Movement Decoding. In: Müller-Putz, G., Rupp, R. (eds) Neuroprosthetics and Brain-Computer Interfaces in Spinal Cord Injury. Springer, Cham. https://doi.org/10.1007/978-3-030-68545-4_10

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