2024
Long-Term Upper-Limb Prosthesis Myocontrol via High-Density sEMG and Incremental Learning
Dario Di Domenico, Nicoló Boccardo, Andrea Marinelli, Michele Canepa, Emanuele Gruppioni, Matteo Laffranchi +1
RA-L 2024
Noninvasive human-machine interfaces such as surface electromyography (sEMG) have long been employed for controlling robotic prostheses. However, classical controllers are limited to few degrees of freedom (DoF). More recently, machine learning methods have been proposed to learn personalized contro