  Precise and elegant coordination of a prosthesis across many degrees of
freedom represents a significant challenge to efficient rehabilitation of
people with limb deficiency. Processing the electrical neural signals,
collected from the surface of the remnant muscles of the stump, is a common way
to initiate and control the different movements available to the artificial
limb. Based on the assumption that there are distinguishable and repeatable
signal patterns among different types of muscular activation, the problem of
the prosthesis control reduces to one of pattern recognition. Widely accepted
classical methods for pattern recognition, however, cannot provide simultaneous
and proportional control of the artificial limb. Here we show that, in
principle, quantum information processing of the neural signals allows us to
overcome the above-mentioned difficulties suggesting a very simple scheme for
myoelectric control of artificial limb with advanced functionalities.
