In order to develop safe training intensity and training methods for the passive balance rehabilitation training 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.
This paper aims to explore the thermal feelings of different cover materials effect on wheelchair cushion comfortableness, and to build a mathematical model for motorized wheelchair cushion comfortableness. By measuring temperature and humidity between the contact face of motorized wheelchair cushion and human body as well as the setting posture adjustment time while cushion cover materials are nylon cloth, leather, fishnets cloth. At the same time, each volunteer took a questionnaire about the comfort of different cushion cover materials. Results showed that fishnets cloth was most comfortable, leather was worst, while nylon cloth was in between the two. The experimental objective data were consistent with the subjective data. We built a back propagation (BP) neural network mathematical model for motorized wheelchair cushion comfortableness. This study will provide objective reference to motorized wheelchair for the designers and users.
Dendritic cells (DCs) are the most potent and specialized antigen-presenting cells (APCs) currently known, which play a crucial role in initiating and amplifying both the innate and adaptive immune responses. During the process of immune function, migration ability of DCs and the number of effector T cells which activated by DCs are closely related to the efficiency of immune function. However, because of the complexity of immune system, in the immune response process caused by the skin chronic inflammatory, much is still unknown about the dynamic changes of cell count with time. Therefore, we created a differential equations model to reflect the initial stages of the immune response process caused by the skin chronic inflammatory via setting the function and initial conditions of parameters. The results showed that the model was able to simulate migration and proliferation of cells in vivo within realistic time scales in accordance with the proliferation and migration efficiency in real terms. In addition, the preliminary model can biologically predict the realistic dynamics of DCs and T cells at different time points. All these results may provide a theoretical reference for studying the immune function of DCs as well as guiding the clinical treatment for immune related diseases further.