Health-status monitoring through analysis of behavioral patterns
Health-status monitoring through analysis of behavioral patterns
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DOI：
10.1109/tsmca.2004.838474
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发表时间：
2005-01-01
影响因子：
--
通讯作者：
Alwan, M
中科院分区：
文献类型：
--
作者：
Barger, TS;Brown, DE;Alwan, M
随着老年人口的迅速增长，有必要支持老年人在家中保持独立和健康生活方式的能力，而不是通过更昂贵和孤立的护理设施。实现这些目标的一种方法是使用环境智能的概念来远程监控老年人的活动和状况。智能住宅项目使用一个基本传感器系统来监控一个人在家里的活动；该系统的原型正在实验对象家中进行测试。我们研究了该系统是否可以用于检测行为模式，并在本文中报告了结果。混合模型被用来建立行为模式的概率模型。混合模型分析的结果然后通过使用由居住者保存的事件日志进行评估。
With the rapid growth of the elderly population, there is a need to support the ability of elders to maintain an independent and healthy lifestyle in their homes rather than through more expensive and isolated care facilities. One approach to accomplish these objectives employs the concepts of ambient intelligence to remotely monitor an elder's activities and condition. The Smart-House project uses a system of basic sensors to monitor a person's in-home activity; a prototype of the system is being tested within a subject's home. We examined whether the system could be used to detect behavioral patterns and report the results in this paper. Mixture models were used to develop a probabilistic model of behavioral patterns. The results of the mixture-model analysis were then evaluated by using a log of events kept by the occupant.