Reliability, validity and clinical usability of a robotic assessment of finger proprioception in persons with multiple sclerosis.


Journal

Multiple sclerosis and related disorders
ISSN: 2211-0356
Titre abrégé: Mult Scler Relat Disord
Pays: Netherlands
ID NLM: 101580247

Informations de publication

Date de publication:
Feb 2023
Historique:
received: 03 01 2022
revised: 31 12 2022
accepted: 13 01 2023
pubmed: 27 1 2023
medline: 15 3 2023
entrez: 26 1 2023
Statut: ppublish

Résumé

Multiple sclerosis often leads to proprioceptive impairments of the hand. However, it is challenging to objectively assess such deficits using clinical methods, thereby also impeding accurate tracking of disease progression and hence the application of personalized rehabilitation approaches. We aimed to evaluate test-retest reliability, validity, and clinical usability of a novel robotic assessment of hand proprioceptive impairments in persons with multiple sclerosis (pwMS). The assessment was implemented in an existing one-degree of freedom end-effector robot (ETH MIKE) acting on the index finger metacarpophalangeal joint. It was performed by 45 pwMS and 59 neurologically intact controls. Additionally, clinical assessments of somatosensation, somatosensory evoked potentials and usability scores were collected in a subset of pwMS. The test-retest reliability of robotic task metrics in pwMS was good (ICC=0.69-0.87). The task could identify individuals with impaired proprioception, as indicated by the significant difference between pwMS and controls, as well as a high impairment classification agreement with a clinical measure of proprioception (85.00-86.67%). Proprioceptive impairments were not correlated with other modalities of somatosensation. The usability of the assessment system was satisfactory (System Usability Scale ≥73.10). The proposed assessment is a promising alternative to commonly used clinical methods and will likely contribute to a better understanding of proprioceptive impairments in pwMS.

Sections du résumé

BACKGROUND BACKGROUND
Multiple sclerosis often leads to proprioceptive impairments of the hand. However, it is challenging to objectively assess such deficits using clinical methods, thereby also impeding accurate tracking of disease progression and hence the application of personalized rehabilitation approaches.
OBJECTIVE OBJECTIVE
We aimed to evaluate test-retest reliability, validity, and clinical usability of a novel robotic assessment of hand proprioceptive impairments in persons with multiple sclerosis (pwMS).
METHODS METHODS
The assessment was implemented in an existing one-degree of freedom end-effector robot (ETH MIKE) acting on the index finger metacarpophalangeal joint. It was performed by 45 pwMS and 59 neurologically intact controls. Additionally, clinical assessments of somatosensation, somatosensory evoked potentials and usability scores were collected in a subset of pwMS.
RESULTS RESULTS
The test-retest reliability of robotic task metrics in pwMS was good (ICC=0.69-0.87). The task could identify individuals with impaired proprioception, as indicated by the significant difference between pwMS and controls, as well as a high impairment classification agreement with a clinical measure of proprioception (85.00-86.67%). Proprioceptive impairments were not correlated with other modalities of somatosensation. The usability of the assessment system was satisfactory (System Usability Scale ≥73.10).
CONCLUSION CONCLUSIONS
The proposed assessment is a promising alternative to commonly used clinical methods and will likely contribute to a better understanding of proprioceptive impairments in pwMS.

Identifiants

pubmed: 36701909
pii: S2211-0348(23)00025-1
doi: 10.1016/j.msard.2023.104521
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104521

Informations de copyright

Copyright © 2023. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of Competing Interests The Authors declare that there is no conflict of interest.

Auteurs

Monika Zbytniewska-Mégret (M)

Rehabilitation Engineering Laboratory, Institute of Robotics and Intelligent Systems, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland. Electronic address: relab.publications@hest.ethz.ch.

Christoph M Kanzler (CM)

Rehabilitation Engineering Laboratory, Institute of Robotics and Intelligent Systems, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland; Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore.

Joke Raats (J)

REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium; Universitair MS Centrum UMSC Hasselt, Pelt, Belgium.

Cigdem Yilmazer (C)

REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium; Universitair MS Centrum UMSC Hasselt, Pelt, Belgium.

Peter Feys (P)

REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium; Universitair MS Centrum UMSC Hasselt, Pelt, Belgium.

Roger Gassert (R)

Rehabilitation Engineering Laboratory, Institute of Robotics and Intelligent Systems, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland; Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore.

Olivier Lambercy (O)

Rehabilitation Engineering Laboratory, Institute of Robotics and Intelligent Systems, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland; Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore.

Ilse Lamers (I)

REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium; Universitair MS Centrum UMSC Hasselt, Pelt, Belgium; Noorderhart Rehabilitation and MS Centre, Pelt, Belgium.

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Classifications MeSH