Improving Fine Control Of Grasping Force During Hand-Object Interactions For A Soft Synergy-Inspired Myoelectric Prosthetic Hand

Keywords

Force control; Grasping; Hand function assessment; Haptic feedback; Neuroprosthetics; Object manipulation

Abstract

The concept of postural synergies of the human hand has been shown to potentially reduce complexity in the neuromuscular control of grasping. By merging this concept with soft robotics approaches, a multi degrees of freedom soft-synergy prosthetic hand [SoftHand-Pro (SHP)] was created. The mechanical innovation of the SHP enables adaptive and robust functional grasps with simple and intuitive myoelectric control from only two surface electromyogram (sEMG) channels. However, the current myoelectric controller has very limited capability for fine control of grasp forces. We addressed this challenge by designing a hybrid-gain myoelectric controller that switches control gains based on the sensorimotor state of the SHP. This controller was tested against a conventional singlegain (SG) controller, as well as against native hand in able-bodied subjects. We used the following tasks to evaluate the performance of grasp force control: (1) pick and place objects with different size, weight, and fragility levels using power or precision grasp and (2) squeezing objects with different stiffness. Sensory feedback of the grasp forces was provided to the user through a non-invasive, mechanotactile haptic feedback device mounted on the upper arm. We demonstrated that the novel hybrid controller enabled superior task completion speed and fine force control over SG controller in object pickand-place tasks. We also found that the performance of the hybrid controller qualitatively agrees with the performance of native human hands.

Publication Date

1-10-2018

Publication Title

Frontiers in Neurorobotics

Volume

11

Issue

JAN

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.3389/fnbot.2017.00071

Socpus ID

85041433864 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85041433864

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