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Conference Paper

Combining Real-Time Brain-Computer Interfacing and Robot Control for Stroke Rehabilitation

MPS-Authors
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Gomez Rodriguez,  M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Peters,  J
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Hill,  J
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Schölkopf,  B
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Grosse-Wentrup,  M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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SIMPAR-2010-Gomez.pdf
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Citation

Gomez Rodriguez, M., Peters, J., Hill, J., Gharabaghi, a., Schölkopf, B., & Grosse-Wentrup, M. (2010). Combining Real-Time Brain-Computer Interfacing and Robot Control for Stroke Rehabilitation. In Brain-Computer Interface Workshop at SIMPAR 2010 (pp. 59-63).


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-BD6A-0
Abstract
Brain-Computer Interfaces based on electrocorticography (ECoG) or electroencephalography (EEG), in combination with robot-assisted active physical therapy, may support traditional rehabilitation procedures for patients with
severe motor impairment due to cerebrovascular brain damage caused by stroke. In this short report, we briefly review the state-of-the art in this exciting new field,
give an overview of the work carried out at the Max Planck Institute for Biological Cybernetics and the University of Tübingen, and discuss challenges that need to be addressed in order to move from basic research to clinical studies.