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Whole Body Center of Mass Feedback in a Reflex-Based Neuromuscular Model Predicts Ankle Strategy During Perturbed Walking.
Article em En | MEDLINE | ID: mdl-34847033
Active prosthetic and orthotic devices have the potential to increase quality of life for individuals with impaired mobility. However, more research into human-like control methods is needed to create seamless interaction between device and user. In forward simulations the reflex-based neuromuscular model (RNM) by Song and Geyer shows promising similarities with real human gait in unperturbed conditions. The goal of this work was to validate and, if needed, extend the RNM to reproduce human kinematics and kinetics during walking in unperturbed and perturbed conditions. The RNM was optimized to reproduce joint torque, calculated with inverse dynamics, from kinematic and force data of unperturbed and perturbed treadmill walking of able-bodied human subjects. Torques generated by the RNM matched closely with torques found from inverse dynamics analysis on human data for unperturbed walking. However, for perturbed walking the modulation of the ankle torque in the RNM was opposite to the modulation observed in humans. Therefore, the RNM was extended with a control module that activates and inhibits muscles around the ankle of the stance leg, based on changes in whole body center of mass velocity. The added module improves the ability of the RNM to replicate human ankle torque response in response to perturbations. This reflex-based neuromuscular model with whole body center of mass velocity feedback can reproduce gait kinetics of unperturbed and perturbed gait, and as such holds promise as a basis for advanced controllers of prosthetic and orthotic devices.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Qualidade de Vida / Tornozelo Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Qualidade de Vida / Tornozelo Idioma: En Ano de publicação: 2021 Tipo de documento: Article