Evaluation of shoulder complex motion-based input strategies for endpoint prosthetic-limb control using dual-task paradigm

Abstract

This article describes the design and evaluation of two comprehensive strategies for endpoint-based control of multiarticulated powered upper-limb prostheses. One method uses residual shoulder motion position; the other solely uses myoelectric signal pattern classification. Both approaches are calibrated for individual users through a short training protocol. The control systems were assessed both quantitatively and qualitatively with use of a functional usability protocol based on a dual-task paradigm. The results revealed that the residual motion-based strategy outperformed the myoelectric signal-based scheme, while neither strategy appeared to significantly increase the mental burden demanded of the users.