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What’s Your Next Move? Detecting Movement Intention for Stroke Rehabilitation

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Brain-Computer Interface Research

Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSELECTRIC))

Abstract

BCIs have recently been identified as a method to promote restorative neuroplastic changes in patients with severe motor impairment, such as after a stroke. In this chapter, we describe a novel therapeutic strategy for hand rehabilitation making use of this method. The approach consists of recording brain activity in cortical motor areas by means of near-infrared spectroscopy, and complementing the cortical signals with physiological data acquired simultaneously. By combining these signals, we aim at detecting the intention to move using a multi-modal classification algorithm. The classifier output then triggers assistance from a robotic device, in order to execute the movement and provide sensory stimulation at the level of the hand as response to the detected motor intention. Furthermore, the cortical data can be used to control audiovisual feedback, which provides a context and a motivating training environment. It is expected that closing the sensorimotor loop with such a brain-body-robot interface will promote neuroplasticity in sensorimotor networks and support the recovery process.

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Author information

Authors and Affiliations

  1. Rehabilitation Engineering Lab, ETH Zurich, Zurich, Switzerland

    R. Zimmermann, O. Lambercy, M. -C. Fluet, J. -C. Metzger, J. Edelmann & R. Gassert

  2. Sensory-Motor Systems Lab, ETH Zurich, Zurich, Switzerland

    L. Marchal-Crespo & R. Riener

  3. Balgrist University Hospital, University of Zurich, Zurich, Switzerland

    L. Marchal-Crespo & R. Riener

  4. Biomedical Optics Research Lab, University Hospital Zurich, Zurich, Switzerland

    R. Zimmermann & M. Wolf

  5. Institute of Neuroinformatics, University of Zurich, Zurich, Switzerland

    J. Brand & K. Eng

Authors
  1. R. Zimmermann
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  2. L. Marchal-Crespo
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  3. O. Lambercy
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  4. M. -C. Fluet
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  5. J. -C. Metzger
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  6. J. Edelmann
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  7. J. Brand
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  8. K. Eng
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  9. R. Riener
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  10. M. Wolf
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  11. R. Gassert
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Corresponding author

Correspondence to R. Zimmermann .

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Editors and Affiliations

  1. Guger Technologies OG, Sierningstrasse 14, Schiedlberg, 4521, Austria

    Christoph Guger

  2. , Cognitive Science Department, University of California, Baltimore Drive 5700Apt 167, San Diego, 91942, California, USA

    Brendan Z. Allison

  3. g.tec Guger Technologies OG, Herbersteinstrasse 60, Graz, 8020, Austria

    Günter Edlinger

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Zimmermann, R. et al. (2013). What’s Your Next Move? Detecting Movement Intention for Stroke Rehabilitation. In: Guger, C., Allison, B., Edlinger, G. (eds) Brain-Computer Interface Research. SpringerBriefs in Electrical and Computer Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36083-1_4

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  • DOI: https://doi.org/10.1007/978-3-642-36083-1_4

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36082-4

  • Online ISBN: 978-3-642-36083-1

  • eBook Packages: EngineeringEngineering (R0)

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