An optimal control framework to predict gait patterns resulting from changes in musculoskeletal properties
Nenhuma Miniatura disponível
Citações na Scopus
0
Tipo de produção
Artigo de evento
Data
2016-08-18
Autores
SANTOS, G. F.
GOMES, A. A.
SACCO, I. C. N.
Marco Ackermann
GOMES, A. A.
SACCO, I. C. N.
Marco Ackermann
Orientador
Periódico
Proceedings of the 6th IASTED International Conference on Modelling, Simulation and Identification, MSI 2016
Título da Revista
ISSN da Revista
Título de Volume
Citação
SANTOS, G. F.; GOMES, A. A.; SACCO, I. C. N. ACKERMANN, M. An optimal control framework to predict gait patterns resulting from changes in musculoskeletal properties. Proceedings of the 6th IASTED International Conference on Modelling, Simulation and Identification, MSI 2016, p. 225-230, August. 2016.
Texto completo (DOI)
Palavras-chave
Resumo
A musculoskeletal model allows the analysis of the human gait and may aid the investigation of different strategies employed by the human body to perform this important task. This study presents a planar multibody model of the musculoskeletal system and an optimal control approach to obtain the time history of motion and muscle activation during the gait. Passive joint moments and muscle properties of the model are modified to represent potential changes caused by different diseases, such as diabetic neuropathy. The system adaptation is predicted on the basis of an optimal control framework and the results show many global adaptations as a response to local changes in the properties of the musculoskeletal system and evidences the great potential of this framework to predict patient adaptations to disease, assistive devices or surgical interventions.