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A modeling method for human standing balance system based on T-S fuzzy identification / 生物医学工程学杂志
Journal of Biomedical Engineering ; (6): 1243-1249, 2014.
Article de Zh | WPRIM | ID: wpr-234422
Bibliothèque responsable: WPRO
ABSTRACT
In order to develop safe training intensity and training methods for the passive balance rehabilitation train- ing system, we propose in this paper a mathematical model for human standing balance adjustment based on T-S fuzzy identification method. This model takes the acceleration of a multidimensional motion platform as its inputs, and human joint angles as its outputs. We used the artificial bee colony optimization algorithm to improve fuzzy C--means clustering algorithm, which enhanced the efficiency of the identification for antecedent parameters. Through some experiments, the data of 9 testees were collected, which were used for model training and model results validation. With the mean square error and cross-correlation between the simulation data and measured data, we concluded that the model was accurate and reasonable.
Sujet(s)
Texte intégral: 1 Base de données: WPRIM Sujet principal: Algorithmes / Analyse de regroupements / Logique floue / Équilibre postural / Modèles théoriques Limites: Humans Langue: Zh Journal: Journal of Biomedical Engineering Année: 2014 Type de document: Article
Texte intégral: 1 Base de données: WPRIM Sujet principal: Algorithmes / Analyse de regroupements / Logique floue / Équilibre postural / Modèles théoriques Limites: Humans Langue: Zh Journal: Journal of Biomedical Engineering Année: 2014 Type de document: Article