Towards falls prevention: A wearable wireless and battery-less sensing and automatic identification tag for real time monitoring of human movements

Towards falls prevention: A wearable wireless and battery-less sensing and automatic identification tag for real time monitoring of human movements
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预防跌倒:可穿戴无线、无电池传感和自动识别标签,用于实时监测人体运动

DOI:
10.1109/embc.2012.6347459
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发表时间:
2012
期刊:
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
影响因子:
--
通讯作者:
R. Visvanathan
R. Visvanathan
中科院分区:
--
文献类型:
--
作者:
D. Ranasinghe;R. L. S. Torres;A. Sample;Joshua R. Smith;K. Hill;R. Visvanathan

文献摘要

被引文献

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医院中的老年患者或住宅护理设施中的居民中的福尔斯相关损伤是一个重大问题,其对所涉及的人造成情感和身体创伤,同时在人口老龄化的国家(例如澳大利亚)中呈现出不断上升的医疗保健费用。使用低成本和隐私保护传感器使能的射频识别(RFID)技术的新方法可能具有提供低成本和有效的技术干预以防止医院中的福尔斯跌倒的潜力。我们概述了可穿戴传感器启用RFID标签的细节,该标签是无电池的,成本低,重量轻,免维护,可以连续佩戴,用于自动和无监督的远程监测急性医院或住院护理的虚弱患者的活动。本文中概述的技术发展构成了为减少急性医院或住院护理设施中的福尔斯跌倒而开发的整体技术干预的一部分。本文概述了技术的细节,基本的算法和结果(其中达到94-100%的准确度)的成功试点试验。
Falls related injuries among elderly patients in hospitals or residents in residential care facilities is a significant problem that causes emotional and physical trauma to those involved while presenting a rising healthcare expense in countries such as Australia where the population is ageing. Novel approaches using low cost and privacy preserving sensor enabled Radio Frequency Identification (RFID) technology may have the potential to provide a low cost and effective technological intervention to prevent falls in hospitals. We outline the details of a wearable sensor enabled RFID tag that is battery free, low cost, lightweight, maintenance free and can be worn continuously for automatic and unsupervised remote monitoring of activities of frail patients at acute hospitals or residents in residential care. The technological developments outlined in the paper forms part of an overall technological intervention developed to reduce falls at acute hospitals or in residential care facilities. This paper outlines the details of the technology, underlying algorithms and the results (where an accuracy of 94-100% was achieved) of a successful pilot trial.