Grasp performance of a soft synergy-based prosthetic hand: A pilot study

Alycia S. Gailey, Sasha Blue Godfrey, Ryan E. Breighner, Karen L. Andrews, Kristin D. Zhao, Antonio Bicchi, Marco Santello

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Current prosthetic hands are frequently rejected in part due to limited functionality and versatility. We assessed the feasibility of a novel prosthetic hand, the SoftHand Pro (SHP), whose design combines soft robotics and hand postural synergies. Able-bodied subjects (n = 23) tracked cursor motion by opening and closing the SHP and performed a grasp-lift-hold-release (GLHR) task with a sensorized cylindrical object of variable weight. The SHP control was driven by electromyographic (EMG) signals from two antagonistic muscles. Although the time to perform the GLHR task was longer for the SHP than native hand for the first few trials (10.2 ± 1.4 s and 2.13 ± 0.09 s, respectively), performance was much faster on subsequent trials (∼5 s). The SHP steady-state grip force was significantly modulated as a function of object weight (p < 0.001). For the native hand, however, peak and steady-state grip forces were modulated to a greater extent (+68% and +91%, respectively). These changes were mediated by the modulation of EMG amplitude and co-contraction. These data suggest that the SHP has a promise for prosthetic applications and point-to-design modifications that could improve the SHP.

Original languageEnglish (US)
Pages (from-to)2407-2417
Number of pages11
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume25
Issue number12
DOIs
StatePublished - Jan 1 2016

Keywords

  • EMG
  • Myoelectric prosthesis
  • Soft robotics

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biomedical Engineering
  • Computer Science Applications

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