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分析智能居家环境中老年人使用便桶扶手进行监测的情况。

Analysis of commode grab bar usage for the monitoring of older adults in the smart home environment.

作者信息

Arcelus Amaya, Holtzman Megan, Goubran Rafik, Sveistrup Heidi, Guitard Paulette, Knoefel Frank

机构信息

Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:6155-8. doi: 10.1109/IEMBS.2009.5334584.

Abstract

The occurrence of falls inside the home is a common yet potentially hazardous issue for adults as they age. Even with the installation of physical aids such as grab bars, weight transfers on and off a toilet or bathtub can become increasingly difficult as a person's level of physical mobility and sense of balance deteriorate. Detecting this deterioration becomes an important goal in fall prevention within a smart home. This paper develops an unobtrusive method of analyzing the usage of toilet grab bars using pressure sensors embedded into the arm rests of a commode. Clinical parameters are successfully extracted automatically from a series of stand-to-sit (StSi) and sit-to-stand (SiSt) transfers performed by a trial group of young and older adults. A preliminary comparison of the parameters indicates differences between the two groups, and aligns well with published characteristics obtained using accelerometers worn on the body. The unobtrusive nature of this method provides a useful tool to be incorporated into a system of continuous monitoring of older adults within the smart home environment.

摘要

对于老年人而言,在家中跌倒的情况很常见,但却可能存在危险。即便安装了诸如扶手之类的辅助设施,随着身体活动能力和平衡感的下降,人们在马桶或浴缸上进行身体重心转移时会变得愈发困难。在智能家居环境中,检测这种身体机能的衰退成为预防跌倒的一个重要目标。本文开发了一种不引人注意的方法,通过嵌入马桶扶手的压力传感器来分析马桶扶手的使用情况。从一组年轻人和老年人进行的一系列从站立到坐下(StSi)以及从坐下到站立(SiSt)的转移动作中,成功自动提取出了临床参数。对这些参数的初步比较表明了两组之间的差异,并且与使用佩戴在身体上的加速度计所获得的已发表特征相吻合。这种方法不引人注意的特性为智能家居环境中纳入对老年人的持续监测系统提供了一个有用的工具。

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