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Visual Cues to Improve Myoelectric Control of Upper Limb Prostheses
In this paper, we develop an automated way to detect stable fixations and show that gaze information is indeed helpful in predicting hand movements.
Adaptive Learning to Speed-Up Control of Prosthetic Hands: a Few Things Everybody Should Know
A number of studies have proposed to use domain adaptation to reduce the training efforts needed to control an upper-limb prosthesis exploiting pre-trained models from prior subjects.
Leveraging over intact priors for boosting control and dexterity of prosthetic hands by amputees
So-called domain adaptation algorithms formalize this strategy and have indeed been shown to significantly reduce the amount of required training data for intact subjects for myoelectric movements classification.
Leveraging Over Priors for Boosting Control of Prosthetic Hands
The aim of this work is to verify, with a computational investigation, if for an amputee this kind of previous experience is useful in order to reduce the training time and boost the prosthetic control.
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