A novel sensory feedback approach to facilitate both predictive and corrective control of grasping force in myoelectric prostheses

Filip Gasparic, Nikola Jorgovanovic, Christian Hofer, Michael F. Russold, Mario Koppe, Darko Stanisic, Strahinja Dosen

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Abstract

Reliable force control is especially important when using myoelectric upper-limb prostheses as the force defines whether an object will be firmly grasped, damaged, or dropped. It is known from human motor control that the grasping of non-disabled subjects is based on a combination of anticipation and feedback correction. Inspired by this insight, the present study proposes a novel approach to provide artificial sensory feedback to the user of a myoelectric prosthesis using vibrotactile stimulation to facilitate both predictive and corrective processes characteristic of grasping in non-disabled people. Specifically, the level of EMG was conveyed to the subjects while closing the prosthesis (predictive strategy), whereas the actual grasping force was transmitted when the prosthesis closed (corrective strategy). To investigate if this combined EMG and force feedback is indeed an effective method to explicitly close the control loop, 16 non-disabled and 3 transradial amputee subjects performed a set of functional tasks, inspired by the 'Box and Block' test, with six target force levels, in three conditions: no feedback, only EMG feedback, and combined feedback. The highest overall performance in non-disabled subjects was obtained with combined feedback (79.6±9.9%), whereas the lowest was achieved with no feedback (53±11.5%). The combined feedback, however, increased the task completion time compared to the other two conditions. A similar trend was obtained also in three amputee subjects. The results, therefore, indicate that the feedback inspired by human motor control is indeed an effective approach to improve prosthesis grasping in realistic conditions when other sources of feedback (vision and audition) are not blocked.

OriginalsprogEngelsk
Artikelnummer10309966
TidsskriftIEEE Transactions on Neural Systems and Rehabilitation Engineering
Vol/bind31
Sider (fra-til)4492-4503
Antal sider12
ISSN1558-0210
DOI
StatusUdgivet - 2023

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