Context-dependent adaptation improves robustness of myoelectric control for upper-limb prostheses

Gauravkumar K. Patel, Janne M. Hahne, Claudio Castellini, Dario Farina, Strahinja Dosen

Research output: Contribution to journalJournal articleResearchpeer-review

12 Citations (Scopus)
246 Downloads (Pure)

Abstract

Objective. Dexterous upper-limb prostheses are available today to restore grasping, but an effective and reliable feed-forward control is still missing. The aim of this work was to improve the robustness and reliability of myoelectric control by using context information from sensors embedded within the prosthesis. Approach. We developed a context-driven myoelectric control scheme (cxMYO) that incorporates the inference of context information from proprioception (inertial measurement unit) and exteroception (force and grip aperture) sensors to modulate the outputs of myoelectric control. Further, a realistic evaluation of the cxMYO was performed online in able-bodied subjects using three functional tasks, during which the cxMYO was compared to a purely machine-learning-based myoelectric control (MYO). Main results. The results demonstrated that utilizing context information decreased the number of unwanted commands, improving the performance (success rate and dropped objects) in all three functional tasks. Specifically, the median number of objects dropped per round with cxMYO was zero in all three tasks and a significant increase in the number of successful transfers was seen in two out of three functional tasks. Additionally, the subjects reported better user experience. Significance. This is the first online evaluation of a method integrating information from multiple on-board prosthesis sensors to modulate the output of a machine-learning-based myoelectric controller. The proposed scheme is general and presents a simple, non-invasive and cost-effective approach for improving the robustness of myoelectric control.

Original languageEnglish
Article number056016
JournalJournal of Neural Engineering
Volume14
Issue number5
Number of pages14
ISSN1741-2560
DOIs
Publication statusPublished - 20 Sept 2017

Keywords

  • context-driven control
  • myoelectric control
  • upper-limb prosthesis

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