Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand

Cristina Piazza*, Ann M. Simon, Kristi L. Turner, Laura A. Miller, Manuel G. Catalano, Antonio Bicchi, Levi J. Hargrove

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Background: State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently, the translation of neuroscientific theories (i.e. postural synergies) in software and hardware architecture of artificial devices is opening new approaches for the design and control of upper-limb prostheses. Methods: Following these emerging principles, previous research on the SoftHand Pro, which embeds one physical synergy, showed promising results in terms of intuitiveness, robustness, and grasping performance. To explore these principles also in hands with augmented capabilities, this paper describes the SoftHand 2 Pro, a second generation of the device with 19 degrees-of-freedom and a second synergistic layer. After a description of the proposed device, the work explores a continuous switching control method based on a myoelectric pattern recognition classifier. Results: The combined system was validated using standardized assessments with able-bodied and, for the first time, amputee subjects. Results show an average improvement of more than 30% of fine grasp capabilities and about 10% of hand function compared with the first generation SoftHand Pro. Conclusions: Encouraging results suggest how this approach could be a viable way towards the design of more natural, reliable, and intuitive dexterous hands.

Original languageEnglish (US)
Article number116
JournalJournal of neuroengineering and rehabilitation
Issue number1
StatePublished - Aug 25 2020


  • Adaptive synergies
  • Bionic hand
  • Myoelectric control
  • Soft robotics

ASJC Scopus subject areas

  • Rehabilitation
  • Health Informatics


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