A modeling method for human standing balance system based on T-S fuzzy identification.
- Author:
Hongrui WANG
;
Kun LIU
;
Jinzhuang XIAO
;
Peng XIONG
- Publication Type:Journal Article
- MeSH:
Algorithms;
Cluster Analysis;
Fuzzy Logic;
Humans;
Models, Theoretical;
Postural Balance
- From:
Journal of Biomedical Engineering
2014;31(6):1243-1249
- CountryChina
- Language:Chinese
-
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.
