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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 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.
Subject(s)
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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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