Real-time evaluation of a myoelectric control method for high-level upper limb amputees based on homologous leg movements.

Abstract

Electromyography-based gesture classification methods for control of advanced upper limb prostheses are limited either to individuals with amputations distal to the elbow or to those willing to undergo targeted muscle reinnervation surgery. Based on the natural similarity between gestures of the lower leg and the arm and on established methods in electromyography-based gesture classification, we propose a noninvasive system with which users control an upper limb prosthesis via homologous movements of the leg and foot. Eight inexperienced able-bodied subjects controlled a simulated robotic arm in a target achievement control (TAC) task with command of up to four degrees of freedom toward targets requiring one motion class. All subjects performed the task with analogous electromyography recording configurations on both the leg and the arm (as a benchmark), achieving slightly better performance with leg control overall. Only a brief demonstration of the arm-leg gesture mapping was necessary for subjects to perform the task, establishing the minimal training time required to begin using the control scheme. Our findings indicate that electromyography-based recognition of leg gestures may be a viable noninvasive prosthesis control option for high-level amputees.