Repetitive control of electrical stimulation for tremor suppression

E. H. Copur, C. T. Freeman, B. Chu, Dina Shona Laila

Research output: Contribution to journalArticle

6 Downloads (Pure)

Abstract

Tremor is a rapid involuntary movement often seen in patients with neurological conditions such as multiple sclerosis and Parkinson's disease. This debilitating oscillation can be suppressed by applying functional electrical stimulation (FES) within a closed-loop control system. However, conventional implementations use classical control methods and have proved capable of only limited performance. This paper establishes the feasibility of embedding repetitive control (RC) action to exploit the capability of learning from experience to completely suppress tremor at the wrist via FES regulated co-contraction of wrist extensors/flexors. A nonlinear model structure and associated identification procedure are first proposed to guarantee stability and performance of the RC system. Then a linearizing control approach is developed to facilitate transparent RC design, together with a mechanism to preserve patients' voluntary intention. Experimental evaluation is performed with both unimpaired and neurologically impaired participants using a validated wrist-rig. For the former group, a novel electromechanical system is employed to induce tremor artificially. Results are bench-marked against a well-known classical filtering technique to establish the efficacy of the RC approach. These confirm that the proposed control system with the developed model identification procedure can increase tremor suppression by 43.3% compared with conventional filtering. In addition, the mechanism reduces the interference of RC action with voluntary motion by 20.2% compared with conventional filtering.
Original languageEnglish
Pages (from-to)540-552
Number of pages13
JournalIEEE Transactions on Control Systems Technology
Volume27
Issue number2
Early online date23 Nov 2017
DOIs
Publication statusPublished - Mar 2019

Fingerprint

Identification (control systems)
Control systems
Closed loop control systems
Model structures

Bibliographical note

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Keywords

  • Functional electrical stimulation (FES)
  • induced tremor
  • repetitive control (RC)
  • tremor suppression

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Repetitive control of electrical stimulation for tremor suppression. / Copur, E. H.; Freeman, C. T.; Chu, B.; Laila, Dina Shona.

In: IEEE Transactions on Control Systems Technology, Vol. 27, No. 2, 03.2019, p. 540-552.

Research output: Contribution to journalArticle

@article{50b826876fb0485ba6733c2f5ac8d3e3,
title = "Repetitive control of electrical stimulation for tremor suppression",
abstract = "Tremor is a rapid involuntary movement often seen in patients with neurological conditions such as multiple sclerosis and Parkinson's disease. This debilitating oscillation can be suppressed by applying functional electrical stimulation (FES) within a closed-loop control system. However, conventional implementations use classical control methods and have proved capable of only limited performance. This paper establishes the feasibility of embedding repetitive control (RC) action to exploit the capability of learning from experience to completely suppress tremor at the wrist via FES regulated co-contraction of wrist extensors/flexors. A nonlinear model structure and associated identification procedure are first proposed to guarantee stability and performance of the RC system. Then a linearizing control approach is developed to facilitate transparent RC design, together with a mechanism to preserve patients' voluntary intention. Experimental evaluation is performed with both unimpaired and neurologically impaired participants using a validated wrist-rig. For the former group, a novel electromechanical system is employed to induce tremor artificially. Results are bench-marked against a well-known classical filtering technique to establish the efficacy of the RC approach. These confirm that the proposed control system with the developed model identification procedure can increase tremor suppression by 43.3{\%} compared with conventional filtering. In addition, the mechanism reduces the interference of RC action with voluntary motion by 20.2{\%} compared with conventional filtering.",
keywords = "Functional electrical stimulation (FES), induced tremor, repetitive control (RC), tremor suppression",
author = "Copur, {E. H.} and Freeman, {C. T.} and B. Chu and Laila, {Dina Shona}",
note = "{\circledC} 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.",
year = "2019",
month = "3",
doi = "10.1109/TCST.2017.2771327",
language = "English",
volume = "27",
pages = "540--552",
journal = "IEEE Transactions on Control Systems Technology",
issn = "1063-6536",
publisher = "Institute of Electrical and Electronics Engineers",
number = "2",

}

TY - JOUR

T1 - Repetitive control of electrical stimulation for tremor suppression

AU - Copur, E. H.

AU - Freeman, C. T.

AU - Chu, B.

AU - Laila, Dina Shona

N1 - © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2019/3

Y1 - 2019/3

N2 - Tremor is a rapid involuntary movement often seen in patients with neurological conditions such as multiple sclerosis and Parkinson's disease. This debilitating oscillation can be suppressed by applying functional electrical stimulation (FES) within a closed-loop control system. However, conventional implementations use classical control methods and have proved capable of only limited performance. This paper establishes the feasibility of embedding repetitive control (RC) action to exploit the capability of learning from experience to completely suppress tremor at the wrist via FES regulated co-contraction of wrist extensors/flexors. A nonlinear model structure and associated identification procedure are first proposed to guarantee stability and performance of the RC system. Then a linearizing control approach is developed to facilitate transparent RC design, together with a mechanism to preserve patients' voluntary intention. Experimental evaluation is performed with both unimpaired and neurologically impaired participants using a validated wrist-rig. For the former group, a novel electromechanical system is employed to induce tremor artificially. Results are bench-marked against a well-known classical filtering technique to establish the efficacy of the RC approach. These confirm that the proposed control system with the developed model identification procedure can increase tremor suppression by 43.3% compared with conventional filtering. In addition, the mechanism reduces the interference of RC action with voluntary motion by 20.2% compared with conventional filtering.

AB - Tremor is a rapid involuntary movement often seen in patients with neurological conditions such as multiple sclerosis and Parkinson's disease. This debilitating oscillation can be suppressed by applying functional electrical stimulation (FES) within a closed-loop control system. However, conventional implementations use classical control methods and have proved capable of only limited performance. This paper establishes the feasibility of embedding repetitive control (RC) action to exploit the capability of learning from experience to completely suppress tremor at the wrist via FES regulated co-contraction of wrist extensors/flexors. A nonlinear model structure and associated identification procedure are first proposed to guarantee stability and performance of the RC system. Then a linearizing control approach is developed to facilitate transparent RC design, together with a mechanism to preserve patients' voluntary intention. Experimental evaluation is performed with both unimpaired and neurologically impaired participants using a validated wrist-rig. For the former group, a novel electromechanical system is employed to induce tremor artificially. Results are bench-marked against a well-known classical filtering technique to establish the efficacy of the RC approach. These confirm that the proposed control system with the developed model identification procedure can increase tremor suppression by 43.3% compared with conventional filtering. In addition, the mechanism reduces the interference of RC action with voluntary motion by 20.2% compared with conventional filtering.

KW - Functional electrical stimulation (FES)

KW - induced tremor

KW - repetitive control (RC)

KW - tremor suppression

UR - http://www.scopus.com/inward/record.url?scp=85036557072&partnerID=8YFLogxK

U2 - 10.1109/TCST.2017.2771327

DO - 10.1109/TCST.2017.2771327

M3 - Article

VL - 27

SP - 540

EP - 552

JO - IEEE Transactions on Control Systems Technology

JF - IEEE Transactions on Control Systems Technology

SN - 1063-6536

IS - 2

ER -