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International Conference on NeuroRehabilitation

ICNR 2020: Converging Clinical and Engineering Research on Neurorehabilitation IV pp 797–801Cite as

Online Continuous Detection of Time-Varying Muscle Synergies

Part of the Biosystems & Biorobotics book series (BIOSYSROB,volume 28)

Abstract

Muscle synergies have been widely used as a compact description of the neuromuscular motor control strategies. The online detection of synergistic activations might therefore improve the feasibility of sEMG-based control algorithms. In this study, a simple online detector of time-varying muscle synergies activation timings is proposed, and its performance is evaluated in a simulated online scenario on a small sample of experimental signals.

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References

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Author information

Authors and Affiliations

  1. Department of Engineering, University of Roma Tre, Rome, Italy

    Simone Ranaldi & Silvia Conforto

  2. Institute for Robotics and Mechatronics, DLR—German Aerospace Center, Weßling, Germany

    Claudio Castellini

  3. Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Rome, Italy

    Andrea D’Avella

  4. Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy

    Andrea D’Avella

Authors
  1. Simone Ranaldi
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  2. Claudio Castellini
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  3. Andrea D’Avella
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  4. Silvia Conforto
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Corresponding author

Correspondence to Simone Ranaldi .

Editor information

Editors and Affiliations

  1. Neural Rehabilitation Group, Cajal Institute, Madrid, Spain

    Dr. Diego Torricelli

  2. Department of Biomedical Engineering, University of Houston, Houston, TX, USA

    Dr. Metin Akay

  3. Department of Biomedical Engineering, Shirley Ryan AbilityLab, Chicago, IL, USA

    Prof. Jose L. Pons

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Cite this paper

Ranaldi, S., Castellini, C., D’Avella, A., Conforto, S. (2022). Online Continuous Detection of Time-Varying Muscle Synergies. In: Torricelli, D., Akay, M., Pons, J.L. (eds) Converging Clinical and Engineering Research on Neurorehabilitation IV. ICNR 2020. Biosystems & Biorobotics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-030-70316-5_127

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  • DOI: https://doi.org/10.1007/978-3-030-70316-5_127

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-70315-8

  • Online ISBN: 978-3-030-70316-5

  • eBook Packages: EngineeringEngineering (R0)

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