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
in Chinese
| WPRIM
| ID: wpr-234422
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.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Algorithms
/
Cluster Analysis
/
Fuzzy Logic
/
Postural Balance
/
Models, Theoretical
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2014
Type:
Article
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