Automated analysis of nursing home observations

被引：32
作者：
Hauptmann, AG [1 ]
Gao, J
Yan, R
Qi, YJ
Yang, J
Wactlar, HD
机构：
[1] Carnegie Mellon Univ, Dept Comp Sci, Pittsburgh, PA 15213 USA
[2] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA
[3] Carnegie Mellon Univ, Sch Comp Sci, Language Technol Inst, Pittsburgh, PA 15213 USA
[4] Carnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15213 USA
来源：
IEEE PERVASIVE COMPUTING | 2004年 / 3卷 / 02期
基金：
美国国家科学基金会;
关键词：
D O I：
10.1109/MPRV.2004.1316813
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The pervasive activity monitoring in a skilled-nursing facility for the accurate assessment and evaluation of behavioral problems for the elderly is analyzed. The pervasive activity monitoring with long-term observation of the elderly in nursing homes can effectively track people over long periods of time. It can identify individuals in tracked events with minimal human help. Pervasive activity monitoring can characterize detailed human activity such as eating or personal hygiene motions.
引用
收藏
页码：15 / 21
页数：7
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