Evaluation of a Simultaneous Myoelectric Control Strategy for a Multi-DoF Transradial Prosthesis

Cristina Piazza*, Matteo Rossi, Manuel G. Catalano, Antonio Bicchi, Levi J. Hargrove

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

While natural movements result from fluid coordination of multiple joints, commercial upper-limb prostheses are still limited to sequential control of multiple degrees of freedom (DoFs), or constrained to move along predefined patterns. To control multiple DoFs simultaneously, a probability-weighted regression (PWR) method has been proposed and has previously shown good performance with intramuscular electromyographic (EMG) sensors. This study aims to evaluate the PWR method for the simultaneous and proportional control of multiple DoFs using surface EMG sensors and compare the performance with a classical direct control strategy. To extract the maximum number of DoFs manageable by a user, a first analysis was conducted in a virtually simulated environment with eight able-bodied and four amputee subjects. Results show that, while using surface EMG degraded the PWR performance for the 3-DoFs control, the algorithm demonstrated excellent achievements in the 2-DoFs case. Finally, the two methods were compared on a physical experiment with amputee subjects using a hand-wrist prosthesis composed of the SoftHand Pro and the RIC Wrist Flexor. Results show comparable outcomes between the two controllers but a significantly higher wrist activation time for the PWR method, suggesting this novel method as a viable direction towards a more natural control of multi-DoFs.

Original languageEnglish (US)
Article number9169706
Pages (from-to)2286-2295
Number of pages10
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume28
Issue number10
DOIs
StatePublished - Oct 2020

Keywords

  • Upper limb prosthesis
  • simultaneous control
  • soft robotics

ASJC Scopus subject areas

  • Internal Medicine
  • Neuroscience(all)
  • Biomedical Engineering

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