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.
Artigo
em Chinês
| WPRIM (Pacífico Ocidental)
| ID: wpr-234422
Biblioteca responsável:
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.
Texto completo:
Disponível
Base de dados:
WPRIM (Pacífico Ocidental)
Assunto principal:
Algoritmos
/
Análise por Conglomerados
/
Lógica Fuzzy
/
Equilíbrio Postural
/
Modelos Teóricos
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2014
Tipo de documento:
Artigo