Position-aware myoelectric prosthesis controllers require long, data-intensive training
routines. Transfer Learning (TL) might reduce training burden. A TL model can be pre …

A commonly cited reason for the high abandonment rate of myoelectric prostheses is a lack
of grip force sensory feedback. Researchers have attempted to restore grip force sensory …

Upper limb robotic (myoelectric) prostheses are technologically advanced, but challenging
to use. In response, substantial research is being done to develop person-specific …

Myoelectric technology has the potential to improve prosthetic device functionality. However,
rejection rates remain high, related to lack of sensory feedback and difficult control strategies …

Artificial limbs are sophisticated devices to assist people with tasks of daily living. Despite
advanced robotic prostheses demonstrating similar motion capabilities to biological limbs …

As reported in 2020, millions of individuals worldwide have some form of upper limb
amputation or congenital loss of limb that impedes execution of everyday actions like …

Modern myoelectric artificial limbs are sophisticated devices with many of the degrees of
freedom of biological limbs. These devices have great potential to provide function for …

Grip force sensory feedback is commonly stated as a desirable feature for upper-limb
myoelectric prosthetics. Many techniques for non-invasive grip force feedback are being …

Upper limb myoelectric prosthesis control is difficult to learn. Virtual reality has seen
increased deployment in recent years for prosthesis training because it is repeatable …

Users of upper limb prostheses face a challenge when attempting to grasp fragile objects
due to an impairment of naturalistic sensory feedback regarding grip strength. Augmented …