Myoelectric Control of Artificial Limb Inspired by Quantum Information Processing

TL;DR

This paper proposes a novel quantum information processing approach to improve myoelectric control of artificial limbs, enabling simultaneous and proportional movements by recognizing neural signal patterns more effectively.

Contribution

It introduces a quantum-inspired scheme for neural signal processing that overcomes classical pattern recognition limitations in prosthetic control.

Findings

Quantum processing can distinguish muscle activation patterns more accurately.

The scheme enables simultaneous and proportional limb movements.

Potential for improved prosthetic control functionalities.

Abstract

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.