基于健康数据挖掘的智能养老床系统设计研究

为解决国内电动养老床功能单一、技术落后等问题,提出一种基于健康数据挖掘的智能养老床系统.首先通过非接触式生命体征传感器采集人体心跳和呼吸信号,压力传感器采集体重信号,基于无线模块将采集的生理参数发送给远程服务器.然后对比分类与聚类方法在心率、呼吸率数据挖掘中的效率,基于k-Means聚类实现健康数据挖掘算法.最后通过聚类算法多次迭代,优化系统参数.实验证明本文提出的基于健康数据挖掘的智能养老床系统不仅能很好地解决传统电动养老床功能单一、技术落后的问题,还能为后续健康护理等提供准确的健康数据保障.

Design of intelligent homecare bed based on health data mining

In order to solve the problems of being functionally simple and technologically outdated of domestic electric homecare bed, a smart homecare bed based on health data mining is proposed. Firstly, the human heartbeat and the breath are collected by the non-contact vital sign sensor, and the weight is collected by the pressure sensor. The collected physiological parameters are transmitted to the remote server by wireless module. Then, by comparing the efficiency of classification and clustering methods in data mining of heart rate and respiratory rate, k-Means clustering algorithm is adopted and implemented for health data mining. Finally, the system parameters are optimized by multiple iterations through the clustering algorithm. The experiment proves that the smart homecare bed system based on health data mining proposed in this paper can not only solve the problems existing in the traditional electric homecare bed, but also provide accurate health data guarantee for subsequent health care service