Closed-loop control of grasping with a myoelectric hand prosthesis: Which are the relevant feedback variables for force control?

Andrei Ninu*, Strahinja Dosen, Silvia Muceli, Frank Rattay, Hans Dietl, Dario Farina

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

94 Citations (Scopus)

Abstract

In closed-loop control of grasping by hand prostheses, the feedback information sent to the user is usually the actual controlled variable, i.e., the grasp force. Although this choice is intuitive and logical, the force production is only the last step in the process of grasping. Therefore, this study evaluated the performance in controlling grasp strength using a hand prosthesis operated through a complete grasping sequence while varying the feedback variables (e.g., closing velocity, grasping force), which were provided to the user visually or through vibrotactile stimulation. The experiments were conducted on 13 volunteers who controlled the Otto Bock Sensor Hand Speed prosthesis. Results showed that vibrotactile patterns were able to replace the visual feedback. Interestingly, the experiments demonstrated that direct force feedback was not essential for the control of grasping force. The subjects were indeed able to control the grip strength, predictively, by estimating the grasping force from the prosthesis velocity of closing. Therefore, grasping without explicit force feedback is not completely blind, contrary to what is usually assumed. In our study we analyzed grasping with a specific prosthetic device, but the outcomes are also applicable for other devices, with one or more degrees- of-freedom. The necessary condition is that the electromyography (EMG) signal directly and proportionally controls the velocity/ grasp force of the hand, which is a common approach among EMG controlled prosthetic devices. The results provide important indications on the design of closed-loop EMG controlled prosthetic systems.

Original languageEnglish
Article number6807741
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume22
Issue number5
Pages (from-to)1041-1052
Number of pages12
ISSN1534-4320
DOIs
Publication statusPublished - 1 Sept 2014
Externally publishedYes

Keywords

  • Closed-loop systems
  • Grasping
  • Haptic interfaces
  • Prosthetic hand
  • Vibrations

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