摘要
针对现有的老人认知评估需要固定周期检验,存在繁琐、执行困难的问题,提出一种智能化的老人认知健康评估方法。该方法基于隐式传感器如门禁,红外等采集数据,融合蒙特利尔认知评估量表数据,并进行分析,以实现连续性的预判老人认知衰退,从而引导老人进行认知评估,解决评估周期长的问题。系统使用Node.js搭建一个基本的数据管理平台框架,Mongo DB进行数据管理,用线性回归拟合传感器数据及评估数据。社区试点部署结果表明,本平台不仅提供了一套评估老人认知下降的有效方法,同时有效实现老人居家智能化危险报警。
Abstract The cognition appraisal for empty nesters require test with fixed cycle which is tedious and difficult to carry out,thus an intelligent assessment method for cognitive health of empty nester is proposed.The method is based on implicit sensors such as access control and infrared to collect data,and is analysed based on Montreal cognition assessment scale to continuous anticipation of cognitive impairment.It can guide the elders to do cognition assessment in terms of long assessment cycle.The system uses Node.js to build the platform framework,MongoDB manages the data,fit and evaluate the sensor data with linear regression.Community pilot deployment results indicate that the platform can not only provide an effective method of assessing the cognitive impairment,but also realize the intellectualized living warning for the elderly.
作者
姚小慧
邵堃
王雯云
孙传能
金柳颀
Yao Xiaohui;Shao Kun;Wang Wenyu;Sun Chuanneng;Jin Liuqi(Intelligent Manufacturing Institute,Hefei University of Technology,Hefei 230009,Anhui,China;School of Computer and Information,Hefei University of Technology,Hefei 230009,Anhui,China)
出处
《计算机应用与软件》
北大核心
2018年第3期70-74,共5页
Computer Applications and Software
基金
安徽省2017年度重点研究与开发计划项目(1704e1002221)
佛山市科技创新团队项目(2015IT100095)
高等学校学科创新引智计划项目(B14025)
关键词
独居老人
认知评估
隐式感知
报警系统
线性回归
Empty nester
Cognitive assessment
Implicit perception
Warning system
Linear regression
