System identification for FES-based tremor suppression

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

Research output: Contribution to journalArticle

1 Citation (Scopus)
21 Downloads (Pure)

Abstract

Tremor is an involuntary motion which is a common complication of Parkinson׳s disease and Multiple Sclerosis. A promising treatment is to artificially contract the muscle through application of induced electrical stimulation. However, existing controllers have either provided only modest levels of suppression or have been applied only in simulation. To enable more advanced, model-based control schemes, an accurate model of the relevant limb dynamics is required, together with identification procedures that are suitable for clinical application. This paper proposes such a solution, explicitly addressing limitations of existing methodologies. These include model structures that (i) neglect critical features, and (ii) restrict the range of admissible control schemes, together with identification procedures that (iii) employ stimulation inputs that are uncomfortable for patients, (iv) are overly complex and time-consuming for clinical use, and (v) cannot be automated. Experimental results confirm the efficacy of the proposed identification procedures, and show that high levels of accuracy can be achieved in a short identification time using test procedures that are suitable for future transference to the clinical domain.
Original languageEnglish
Pages (from-to)45-59
JournalEuropean Journal of Control
Volume27
DOIs
Publication statusPublished - 12 Dec 2015

Fingerprint

Identification (control systems)
Model structures
Muscle
Controllers

Bibliographical note

CC BY-NC-ND license

Keywords

  • Tremor
  • System identification
  • Hammerstein structure
  • Functional electrical stimulation
  • Muscle model
  • Linearisation

Cite this

System identification for FES-based tremor suppression. / Copur, E. H.; Freeman, C. T.; Chu, B.; Laila, Dina Shona.

In: European Journal of Control, Vol. 27, 12.12.2015, p. 45-59.

Research output: Contribution to journalArticle

Copur, E. H. ; Freeman, C. T. ; Chu, B. ; Laila, Dina Shona. / System identification for FES-based tremor suppression. In: European Journal of Control. 2015 ; Vol. 27. pp. 45-59.
@article{42c3be5ab7c04d52aa9793b8eed27f99,
title = "System identification for FES-based tremor suppression",
abstract = "Tremor is an involuntary motion which is a common complication of Parkinson׳s disease and Multiple Sclerosis. A promising treatment is to artificially contract the muscle through application of induced electrical stimulation. However, existing controllers have either provided only modest levels of suppression or have been applied only in simulation. To enable more advanced, model-based control schemes, an accurate model of the relevant limb dynamics is required, together with identification procedures that are suitable for clinical application. This paper proposes such a solution, explicitly addressing limitations of existing methodologies. These include model structures that (i) neglect critical features, and (ii) restrict the range of admissible control schemes, together with identification procedures that (iii) employ stimulation inputs that are uncomfortable for patients, (iv) are overly complex and time-consuming for clinical use, and (v) cannot be automated. Experimental results confirm the efficacy of the proposed identification procedures, and show that high levels of accuracy can be achieved in a short identification time using test procedures that are suitable for future transference to the clinical domain.",
keywords = "Tremor, System identification, Hammerstein structure, Functional electrical stimulation, Muscle model, Linearisation",
author = "Copur, {E. H.} and Freeman, {C. T.} and B. Chu and Laila, {Dina Shona}",
note = "CC BY-NC-ND license",
year = "2015",
month = "12",
day = "12",
doi = "10.1016/j.ejcon.2015.12.003",
language = "English",
volume = "27",
pages = "45--59",
journal = "European Journal of Control",
issn = "0947-3580",
publisher = "Elsevier",

}

TY - JOUR

T1 - System identification for FES-based tremor suppression

AU - Copur, E. H.

AU - Freeman, C. T.

AU - Chu, B.

AU - Laila, Dina Shona

N1 - CC BY-NC-ND license

PY - 2015/12/12

Y1 - 2015/12/12

N2 - Tremor is an involuntary motion which is a common complication of Parkinson׳s disease and Multiple Sclerosis. A promising treatment is to artificially contract the muscle through application of induced electrical stimulation. However, existing controllers have either provided only modest levels of suppression or have been applied only in simulation. To enable more advanced, model-based control schemes, an accurate model of the relevant limb dynamics is required, together with identification procedures that are suitable for clinical application. This paper proposes such a solution, explicitly addressing limitations of existing methodologies. These include model structures that (i) neglect critical features, and (ii) restrict the range of admissible control schemes, together with identification procedures that (iii) employ stimulation inputs that are uncomfortable for patients, (iv) are overly complex and time-consuming for clinical use, and (v) cannot be automated. Experimental results confirm the efficacy of the proposed identification procedures, and show that high levels of accuracy can be achieved in a short identification time using test procedures that are suitable for future transference to the clinical domain.

AB - Tremor is an involuntary motion which is a common complication of Parkinson׳s disease and Multiple Sclerosis. A promising treatment is to artificially contract the muscle through application of induced electrical stimulation. However, existing controllers have either provided only modest levels of suppression or have been applied only in simulation. To enable more advanced, model-based control schemes, an accurate model of the relevant limb dynamics is required, together with identification procedures that are suitable for clinical application. This paper proposes such a solution, explicitly addressing limitations of existing methodologies. These include model structures that (i) neglect critical features, and (ii) restrict the range of admissible control schemes, together with identification procedures that (iii) employ stimulation inputs that are uncomfortable for patients, (iv) are overly complex and time-consuming for clinical use, and (v) cannot be automated. Experimental results confirm the efficacy of the proposed identification procedures, and show that high levels of accuracy can be achieved in a short identification time using test procedures that are suitable for future transference to the clinical domain.

KW - Tremor

KW - System identification

KW - Hammerstein structure

KW - Functional electrical stimulation

KW - Muscle model

KW - Linearisation

U2 - 10.1016/j.ejcon.2015.12.003

DO - 10.1016/j.ejcon.2015.12.003

M3 - Article

VL - 27

SP - 45

EP - 59

JO - European Journal of Control

JF - European Journal of Control

SN - 0947-3580

ER -