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Model-based control of individual finger movements for prosthetic hand function

Model-based control of individual finger movements for prosthetic hand function Thumbnail


Abstract

Abstract Prosthetic devices for hand difference have advanced considerably in recent years, to the point where the mechanical dexterity of a state-of-the-art prosthetic hand approaches that of the natural hand. Control options for users, however, have not kept pace, meaning that the new devices are not used to their full potential. Promising developments in control technology reported in the literature have met with limited commercial and clinical success. We have previously described a biomechanical model of the hand that could be used for prosthesis control. In this study, we report on three key elements of the biomechanical simulations relevant to prosthesis control: we show the performance of the model in replicating recorded hand kinematics and find average correlations of 0.89 between modelled and recorded motions; we show that the computational performance of the simulations is fast enough to achieve real-time control with a robotic hand in the loop; and we describe the use of the model for controlling object gripping. Despite some limitations in accessing sufficient driving signals, the model performance shows promise as a controller for prosthetic hands when driven with recorded EMG signals. We identify areas for future work to address these limitations.

Acceptance Date May 7, 2019
Publication Date Jan 20, 2020
Publicly Available Date Mar 28, 2024
Journal IEEE Transactions on Neural Systems and Rehabilitation Engineering
Print ISSN 1534-4320
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Pages 612-620
DOI https://doi.org/10.1101/629246
Publisher URL https://doi.org/10.1109/TNSRE.2020.2967901

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