摘要
针对消化道内温度高精度测量问题,设计了一种可用于测量人体消化道温度的微型无创电子遥测胶囊。为实现其高精度测量,利用中值滤波技术预处理样本数据,去除外界的干扰噪声。然后,建立基于径向基函数(RBF)神经网络温度补偿模型,实现了对胃肠道温度的非线性测量。实验证明:利用中值滤波技术和RBF神经网络的补偿模型,测温精度明显高于一般的线性补偿方法,可以满足胃肠消化道内测温系统的要求。
In order to address the problem of high precision temperature detection in gastrointestinal tract, a miniature non-invasive temperature detecting capsule for gastrointestinal tract is presented. In order to attend high precision,a median filter is used to settle sample data and reduce disturbing noise. And a compensation model based on the theory of RBF neural network is built to test the non-liner temperature of gastrointestinal tract. The experiments conclude that the accuracy of the system based on median filter and RBF networks compensation model is higher than the normal liner temperature compensation methods. The temperature detecting capsule can fulfill the requirement of temperature detecting capsule.
出处
《传感器与微系统》
CSCD
北大核心
2007年第9期83-85,88,共4页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(30570485)
国家"863"高技术研究发展计划资助项目(2004AA404013)
关键词
RBF神经网络
温度测量
电子胶囊
无创检测
RBF neural networks
temperature test
electronic capsule
noninvasive test
