The University of Southampton
University of Southampton Institutional Repository

Repetitive control of electrical stimulation for tremor suppression

Repetitive control of electrical stimulation for tremor suppression
Repetitive control of electrical stimulation for tremor suppression
Tremor is a rapid uncontrollable back-and-forth movement of a body part often seen in patients with neurological conditions such as Multiple Sclerosis (MS) and Parkinson’s disease. This debilitating oscillation can be suppressed by applying functional electrical stimulation (FES) within a closedloop control system. However current implementations use classical control methods and have proved capable of only limited performance. This paper develops a novel application of repetitive control (RC) that exploits the capability of learning from experience to enable complete suppression of the tremor. The proposed control structure is applied to suppress tremor at the wrist via FES regulated co-contraction of wrist extensors/flexors. Experimental evaluation is performed using a validated wristrig and results are compared against classical feedback control designs to establish the efficacy of the approach.
1063-6536
540-552
Copur, Engin
34d7cc9e-63b2-4233-a3ba-0293f572f961
Freeman, Christopher
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Laila, Dina
41aa5cf9-3ec2-4fdf-970d-a0a349bfd90c
Copur, Engin
34d7cc9e-63b2-4233-a3ba-0293f572f961
Freeman, Christopher
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Laila, Dina
41aa5cf9-3ec2-4fdf-970d-a0a349bfd90c

Copur, Engin, Freeman, Christopher, Chu, Bing and Laila, Dina (2019) Repetitive control of electrical stimulation for tremor suppression. IEEE Transactions on Control Systems Technology, 27 (2), 540-552. (doi:10.1109/TCST.2017.2771327).

Record type: Article

Abstract

Tremor is a rapid uncontrollable back-and-forth movement of a body part often seen in patients with neurological conditions such as Multiple Sclerosis (MS) and Parkinson’s disease. This debilitating oscillation can be suppressed by applying functional electrical stimulation (FES) within a closedloop control system. However current implementations use classical control methods and have proved capable of only limited performance. This paper develops a novel application of repetitive control (RC) that exploits the capability of learning from experience to enable complete suppression of the tremor. The proposed control structure is applied to suppress tremor at the wrist via FES regulated co-contraction of wrist extensors/flexors. Experimental evaluation is performed using a validated wristrig and results are compared against classical feedback control designs to establish the efficacy of the approach.

Text
IEEE_Trans_CST_EHC_Revised_CF - Accepted Manuscript
Download (5MB)

More information

Accepted/In Press date: 1 November 2017
e-pub ahead of print date: 23 November 2017
Published date: March 2019
Organisations: Vision, Learning and Control, EEE

Identifiers

Local EPrints ID: 401029
URI: http://eprints.soton.ac.uk/id/eprint/401029
ISSN: 1063-6536
PURE UUID: f99887d4-961f-49c1-a161-81f4de5fa65a
ORCID for Bing Chu: ORCID iD orcid.org/0000-0002-2711-8717

Catalogue record

Date deposited: 01 Oct 2016 13:33
Last modified: 07 Oct 2020 04:02

Export record

Altmetrics

Contributors

Author: Engin Copur
Author: Christopher Freeman
Author: Bing Chu ORCID iD
Author: Dina Laila

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.

×