HUANG Chen, PAN Yong-cai, LI Ke-wei, et al. Design of intelligent medical model based on sensor clustering data mining in IoT[J]. 2014, 33(4): 76-79. DOI: 10.13873/j.1000-97872014.04.025.
基于传感器聚类数据挖掘的物联网智慧医疗模型设计
摘要
现代智慧医疗需要操作简洁、反应迅速
能够提供智慧诊断的信息化平台
提出基于物联网无线传感器技术的智慧医疗模型。系统利用附着在患者身上的各类传感器采集到的生理信息数据
采用基于密度的带有噪声的空间聚类(DBSCAN)算法的数据分析方法
用非线性映射把患者的生理信息数据转换到高纬度的特征空间
对变换后的矢量数据进行聚类分析
从而提升聚类结果并有效辅助医务人员进行诊断。
Abstract
Modern intelligent medical care needs an information platform which can provide easy operation
fast response
and intellective diagnose
so propose intelligent medical model based on Internet of things( IoT) wireless sensor technology. This system collects physiological datas by intelligent sensors attached to patients
and adopts data analysis method based on density clustering density-based spatial clustering of applications with noise( DBSCAN) algorithm using space transformation
which converts physiological information to a high dimension feature space using nonlinear mapping
and carry out clustering analysis on transformed vector data
to promote clustering efficiency and assist medical staffs to diagnose.
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