动态生理信息融合在人体健康评价系统的应用

针对人体健康状况实时评价问题，将生理医学理论与信息融合技术相结合，设计了一种基于动态生理信息融合的健康评价系统。利用扩展的卡尔曼滤波辅助方法进行预处理及特征提取，将模糊逻辑引进神经网络，推进了模型一致性推理过程，选取基于数值优化改进的BP算法。仿真结果及健康增进型运动平台的实际应用表明该系统能够快速、准确完成人体健康状况的评价。

Health evaluation system based on dynamic physiological information fusion

A health evaluating system based on the fusion technology and physiological medicine theory is designed.The extended Kalman filtering is used to complete the pre-processment and feature extraction,the fuzzy logic works in the neural networks to boost coincidence illation,the amelioration BP arithmetic based on numerical optimization is adopted.The simulation result and the application in the enhancing motion platform indicate that the system can complete the evaluation on the states of health fast and accurately,and can meet the application requires.