The University of Southampton
University of Southampton Institutional Repository

Application of multiple model adaptive control to upper limb stroke rehabilitation

Brend, O., Freeman, C.T. and French, M. (2012) Application of multiple model adaptive control to upper limb stroke rehabilitation At IEEE Multiconference on Systems and Control (MSC 2012), Croatia. 03 - 05 Oct 2012. 6 pp, pp. 69-74.

Record type: Conference or Workshop Item (Paper)

Abstract

Impaired arm function has a significant impact on the quality of life of stroke sufferers. Research has shown that the application of functional electrical stimulation (FES) to assist their movement over repeated attempts at a task is effective in restoring function. However, current FES control systems lack robustness to changes in plant dynamics caused by fatigue and spasticity. This paper details the application of a multiple model adaptive control algorithm that has the potential to overcome this problem. It is shown in an experimental setting that an adaptive estimation mechanism is able to detect changes in the true plant through optimal disturbance estimation. Finally, the performance of the algorithm is compared with that of fixed optimal controllers. These initial results suggest that the application of estimation-based multiple model switched adaptive control (EMMSAC) can increase the potential of FES based rehabilitation through improved controller accuracy.

PDF BrendMSC2012.pdf - Other
Restricted to Registered users only
Download (1MB)

More information

Published date: 4 October 2012
Venue - Dates: IEEE Multiconference on Systems and Control (MSC 2012), Croatia, 2012-10-03 - 2012-10-05
Organisations: EEE, Southampton Wireless Group

Identifiers

Local EPrints ID: 340088
URI: http://eprints.soton.ac.uk/id/eprint/340088
PURE UUID: 0f59e036-c99a-477d-a1c1-dc95b56ea307

Catalogue record

Date deposited: 09 Jun 2012 23:00
Last modified: 18 Jul 2017 05:50

Export record

Contributors

Author: O. Brend
Author: C.T. Freeman
Author: M. French

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×