Identification of the best strategy to command variable stiffness using electromyographic signals.

Journal: Journal of neural engineering
PMID: 31958778

Abstract

OBJECTIVE: In the last decades, many EMG-controlled robotic devices were developed. Since stiffness control may be required to perform skillful interactions, different groups developed devices whose stiffness is real-time controlled based on EMG signal samples collected from the operator. However, this control strategy may be fatiguing. In this study, we proposed and experimentally validated a novel stiffness control strategy, based on the average muscle co-contraction estimated from EMG samples collected in the previous 1 or 2 s.

Authors

  • Daniele Borzelli
    Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy. Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy. Author to whom any correspondence should be addressed.
  • Etienne Burdet
  • Stefano Pastorelli
  • Andrea d'Avella
  • Laura Gastaldi

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