title: [A modeling method for human standing balance system based on T-S fuzzy identification].
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.
authors: Hongrui
authors: H
authors: Wang
authors: Kun
authors: K
authors: Liu
authors: Jinzhuang
authors: J
authors: Xiao
authors: Peng
authors: P
authors: Xiong
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D017143:Fuzzy Logic; D006801:Humans; D008962:Models, Theoretical; D004856:Postural Balance