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.
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