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EMG-Based Detection of User’s Intentions for Human-Machine Shared Control of an Assistive Upper-Limb Exoskeleton

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Wearable Robotics: Challenges and Trends

Part of the book series: Biosystems & Biorobotics ((BIOSYSROB,volume 16))

Abstract

To assist people with disabilities, exoskeletons must be provided with human-machine interfaces (HMI) capable to identify the user’s intentions and enable cooperative interaction. Electromyographic (EMG) signals could be suitable for this purpose, but their usability and effectiveness for shared control schemes in assistive devices is currently unclear. Here we developed advanced machine learning (ML) algorithms for detecting the user’s motion intention and decoding the intended movement direction, and discuss their applicability to the control of an upper-limb exoskeleton used as an assistive device for people with severe arm disabilities.

This work was supported by the AIDE Project GA 645322, funded by the EU H2020 Framework Programme for Research and Innovation, and by the RONDA Project, funded by Regione Toscana PAR FAS 2007-2013.

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Authors and Affiliations

  1. Biorobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy

    A. Accogli, L. Grazi, S. Crea, A. Panarese, J. Carpaneto, N. Vitiello & S. Micera

  2. Center for Neuroprosthetics and Institute of Bioengineering, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland

    S. Micera

Authors
  1. A. Accogli
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  2. L. Grazi
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  3. S. Crea
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  4. A. Panarese
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  5. J. Carpaneto
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  6. N. Vitiello
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  7. S. Micera
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Corresponding author

Correspondence to A. Panarese .

Editor information

Editors and Affiliations

  1. Spanish National Research Council, Cajal Institute Spanish National Research Council, Madrid, Spain

    José González-Vargas

  2. Spanish National Research Council, Cajal Institute Spanish National Research Council, Madrid, Spain

    Jaime Ibáñez

  3. Cullen College of Engineering, University of Houston Cullen College of Engineering, Houston, Texas, USA

    Jose L. Contreras-Vidal

  4. University of Twente , Enschede, The Netherlands

    Herman van der Kooij

  5. Spanish National Research Council, Cajal Institute Spanish National Research Council, Madrid, Spain

    José Luis Pons

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© 2017 Springer International Publishing AG

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Accogli, A. et al. (2017). EMG-Based Detection of User’s Intentions for Human-Machine Shared Control of an Assistive Upper-Limb Exoskeleton. In: González-Vargas, J., Ibáñez, J., Contreras-Vidal, J., van der Kooij, H., Pons, J. (eds) Wearable Robotics: Challenges and Trends. Biosystems & Biorobotics, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-319-46532-6_30

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  • DOI: https://doi.org/10.1007/978-3-319-46532-6_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46531-9

  • Online ISBN: 978-3-319-46532-6

  • eBook Packages: EngineeringEngineering (R0)

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