Wearable sensors for reliable fall detection

被引：224

作者：

Chen, Jay ^{[1
]}

Kwong, Karric ^{[1
]}

Chang, Dennis ^{[1
]}

Luk, Jerry ^{[1
]}

Bajcsy, Ruzena ^{[1
]}

机构：

[1] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA

来源：

2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7 | 2005年

关键词：

D O I：

10.1109/IEMBS.2005.1617246

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Unintentional falls are a common cause of severe injury in the elderly population. By introducing small, non-invasive sensor motes in conjunction with a wireless network, the Ivy Project aims to provide a path towards more independent living for the elderly. Using a small device worn on the waist and a network of fixed motes in the home environment, we can detect the occurrence of a fall and the location of the victim. Low-cost and low-power MEMS accelerometers are used to detect the fall while RF signal strength is used to locate the person.

引用

页码：3551 / 3554

页数：4

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