Traumatic events, which lead to the loss of a limb, implies the interruption of the bidirectional communication between the lost limb and the brain. It causes impairments related to both motor control and sensory feedback which outcome in severe consequences from a functional and social point of view.

A neuroprosthesis could lead to substantial enhancements in the quality of life for individuals with limb loss, but current solutions are still affected by important limitations. A pivotal consideration involves reimagining the interface with the nervous system, striving to achieve the utmost naturalness and minimal invasiveness. The main challenges in motion intention recognition are related to the acquisition of reliable signals and the development of decoding approaches that lead to a natural and intuitive prosthesis control. Several solutions, in terms of the technology adopted to acquire the electromyographic signals and the approaches to retrieve the motion intention, have been proposed. 

The restoration of sensory feedback has also a fundamental role in prosthesis use since it has been demonstrated to reduce visual burden and improve motor capabilities. Different invasive and non-invasive interfaces and several encoding strategies have been proposed in literature for eliciting different sensations by stimulating mainly the Peripheral Nervous System. Despite several advancements have been made in this field, several aspects of sensory feedback, made up of sensory transduction, encoding strategy, stimulation hardware and neural interface, require improvements to replace the complete functionality of the lost limbs. 

This workshop aims at presenting the current issues and at envisioning the upcoming breakthroughs in upper and lower limb prosthetic devices. The workshop will discuss the state-of-the-art of interfacing technologies, closed loop control strategies, sensory encoding, myoelectric control, simulation and modeling applied to the prosthetic field, and will point out current challenges for an effective and reliable prosthetic device. 

• User motion intention detection;

• Myoelectric and motion control

• Invasive and non-invasive interfaces

• Closed loop prostheses

• Somatosensory feedback for prosthetics 

• Neurocomputational models

• Acceptability and reliability