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Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
Published on: January 7, 2019
Sensing Muscle Deformation for Upper-Limb Prosthetic Control: A Narrative Review
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Hand loss profoundly affects daily function and psychological well-being, motivating decades of research into prosthetic technologies and sensing strategies aimed at restoring intuitive and reliable control of artificial limbs. While surface electromyography has long dominated this field, limitations such as poor signal resolution and instability restrict its effectiveness. These challenges have motivated the development of alternative paradigms that leverage biomechanical, rather than purely electrophysiological, signals. Among them, displacement-based approaches, which exploit remnant muscle deformations, show promise for overcoming current barriers and enhancing the efficacy of human-machine interfaces. Here, we review displacement-based prosthetic control strategies that have progressed to clinical testing in individuals with transradial amputation, specifically sonomyography, force myography, mechanomyography and myokinetic interfaces. We highlight their technological principles, reported outcomes, and the challenges that remain for widespread clinical adoption. This review underscores the potential of displacement-based control strategies, but also identifies some common challenges that need to be addressed to enhance accuracy and robustness during daily use.

