Predictive simulation of post-stroke gait with functional electrical stimulation.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
01 11 2021
01 11 2021
Historique:
received:
24
06
2021
accepted:
14
10
2021
entrez:
2
11
2021
pubmed:
3
11
2021
medline:
21
1
2022
Statut:
epublish
Résumé
Post-stroke patients present various gait abnormalities such as drop foot, stiff-knee gait (SKG), and knee hyperextension. Functional electrical stimulation (FES) improves drop foot gait although the mechanistic basis for this effect is not well understood. To answer this question, we evaluated the gait of a post-stroke patient walking with and without FES by inverse dynamics analysis and compared the results to an optimal control framework. The effect of FES and cause-effect relationship of changes in knee and ankle muscle strength were investigated; personalized muscle-tendon parameters allowed the prediction of pathologic gait. We also predicted healthy gait patterns at different speeds to simulate the subject walking without impairment. The passive moment of the knee played an important role in the estimation of muscle force with knee hyperextension, which was decreased during FES and knee extensor strengthening. Weakening the knee extensors and strengthening the flexors improved SKG. During FES, weak ankle plantarflexors and strong ankle dorsiflexors resulted in increased ankle dorsiflexion, which reduced drop foot. FES also improved gait speed and reduced circumduction. These findings provide insight into compensatory strategies adopted by post-stroke patients that can guide the design of individualized rehabilitation and treatment programs.
Identifiants
pubmed: 34725376
doi: 10.1038/s41598-021-00658-z
pii: 10.1038/s41598-021-00658-z
pmc: PMC8560756
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
21351Subventions
Organisme : Deutsche Forschungsgemeinschaft
ID : 316739714
Organisme : Agence Nationale de la Recherche
ID : 16-CE92-0042
Informations de copyright
© 2021. The Author(s).
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