Multiple sensor outputs and computational intelligence towards estimating state and speed for control of lower limb prostheses

Date

2014-09-10

Advisors

Journal Title

Journal ISSN

ISSN

DOI

Volume Title

Publisher

Proceedings of the 14th Annual Workshop on Computational Intelligence (UKCI'14)

Type

Conference

Peer reviewed

Yes

Abstract

For as long as people have been able to survive limb threatening injuries prostheses have been created. Modern lower limb prostheses are primarily controlled by adjusting the amount of damping in the knee to bend in a suitable manner for walking and running. Often the choice of walking state or running state has to be controlled manually by pressing a button. This paper examines how this control could be improved using sensors attached tofa the limbs of two volunteers. The signals from the sensors had features extracted which were passed through a computational intelligence system. The system was used to determine whether the volunteer was walking or running and their movement speed. Two new features are presented which identify the movement states of standing, walking and running and the movement speed of the volunteer. The results suggest that the control of the prosthetic limb could be improved.

Description

Keywords

Movement state detection, Electromyographic Signals, Prosthetic, Neural Networks, Signal Processing, Multiple Sensor outputs, Computational Intelligence, Feature Extraction, Pattern Recognition

Citation

Hardaker, P.A., Passow, B.N., Elizondo, D. (2014) Multiple sensor outputs and computational intelligence towards estimating state and speed for control of lower limb prostheses. Computational Intelligence (UKCI), 2014 14th UK Workshop on , pp.1-8, 8-10 Sept. 2014

Rights

Research Institute

Institute of Artificial Intelligence (IAI)