The University of Southampton
University of Southampton Institutional Repository

Identification of the Dynamics of Human Arms after Stroke

Le, Fengmin, Markovsky, Ivan, Freeman, Christopher and Rogers, Eric (2008) Identification of the Dynamics of Human Arms after Stroke At 23rd IAR Workshop on Advanced Control and Diagnosis, United Kingdom. 27 - 28 Nov 2008.

Record type: Conference or Workshop Item (Paper)

Abstract

The design of controllers to enable the application of Functional Electrical Stimulation as part of a rehabilitation programme for stroke patients requires an accurate model of electrically stimulated muscle. In this paper, nonlinear dynamics of the electrically stimulated muscle under isometric conditions is investigated, leading to the requirement to identify a Hammerstein model structure. Here we develop a two-stage identification method based on a preliminary construction of the linear part that is used as an initial estimate. Then the two-stage method is applied to identify the nonlinear part and optimize the linear part. The traditional ramp deconvolution method are implemented here and compared with the proposed method using a simulated muscle system that is based on experimental data from stroke patients. The results show that the proposed method outperforms the other one when implemented on the simulated muscle system with different noise levels.

PDF IAR_paper_ref.pdf - Other
Download (250kB)

More information

Submitted date: November 2008
Additional Information: Event Dates: 27-28 November 2008
Venue - Dates: 23rd IAR Workshop on Advanced Control and Diagnosis, United Kingdom, 2008-11-27 - 2008-11-28
Organisations: EEE, Southampton Wireless Group

Identifiers

Local EPrints ID: 266916
URI: http://eprints.soton.ac.uk/id/eprint/266916
PURE UUID: d3302280-6f78-4ec9-a52d-996605ae140c

Catalogue record

Date deposited: 14 Nov 2008 22:00
Last modified: 18 Jul 2017 07:10

Export record

Contributors

Author: Fengmin Le
Author: Ivan Markovsky
Author: Eric Rogers

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.

×