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家居智能:主动与独立——老年人长寿的智能传感器整合。

HDOMO: Smart Sensor Integration for an Active and Independent Longevity of the Elderly.

机构信息

Department of Information Engineering - Università Politecnica delle Marche, I-60131 Ancona, Italy.

出版信息

Sensors (Basel). 2017 Nov 13;17(11):2610. doi: 10.3390/s17112610.

DOI:10.3390/s17112610
PMID:29137174
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5713030/
Abstract

The aim of this paper is to present the main results of HDOMO, an Ambient Assisted Living (AAL) project that involved 16 Small and Medium Enterprises (SMEs) and 2 research institutes. The objective of the project was to create an autonomous and automated domestic environment, primarily for elderly people and people with physical and motor disabilities. A known and familiar environment should help users in their daily activities and it should act as a virtual caregiver by calling, if necessary, relief efforts. Substantially, the aim of the project is to simplify the life of people in need of support, while keeping them autonomous in their private environment. From a technical point of view, the project provides the use of different Smart Objects (SOs), able to communicate among each other, in a cloud base infrastructure, and with the assisted users and their caregivers, in a perspective of interoperability and standardization of devices, usability and effectiveness of alarm systems. In the state of the art there are projects that achieve only a few of the elements listed. The HDOMO project aims to achieve all of them in one single project effectively. The experimental trials performed in a real scenario demonstrated the accuracy and efficiency of the system in extracting and processing data in real time to promptly acting, and in providing timely response to the needs of the user by integrating and confirming main alarms with different interoperable smart sensors. The article proposes a new technique to improve the accuracy of the system in detecting alarms using a multi-SO approach with information fusion between different devices, proving that this architecture can provide robust and reliable results on real environments.

摘要

本文旨在介绍 HDOMO 的主要成果,HDOMO 是一个安老及辅助生活(AAL)项目,涉及 16 家中小企业(SMEs)和 2 家研究机构。该项目的目的是创建一个自主和自动化的家庭环境,主要面向老年人和身体或运动有障碍的人士。一个已知和熟悉的环境应该有助于用户进行日常活动,并在必要时通过呼叫来充当虚拟护理人员。该项目的主要目标是简化有需要的人的生活,同时使他们在私人环境中保持自主。从技术角度来看,该项目提供了使用不同的智能物体(SOs),能够在云基础架构中相互通信,并与辅助用户及其护理人员进行交互,实现设备的互操作性和标准化、可用性和报警系统的有效性。在现有技术中,有一些项目仅能实现列出的几个要素。HDOMO 项目旨在有效地在一个单一项目中实现所有这些目标。在真实场景中进行的实验性试验表明,该系统在实时提取和处理数据方面的准确性和效率,通过整合和确认主要警报与不同互操作的智能传感器,及时响应用户的需求。本文提出了一种新技术,通过使用多 SO 方法和不同设备之间的信息融合来提高系统检测警报的准确性,证明这种架构可以在真实环境中提供稳健可靠的结果。

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本文引用的文献

1
An Electromagnetic Sensor for the Autonomous Running of Visually Impaired and Blind Athletes (Part II: The Wearable Device).用于视障和盲人运动员自主运行的电磁传感器(第二部分:可穿戴设备)。
Sensors (Basel). 2017 Feb 16;17(2):381. doi: 10.3390/s17020381.
2
A smart kitchen for ambient assisted living.智能厨房助力安养环境。
Sensors (Basel). 2014 Jan 17;14(1):1629-53. doi: 10.3390/s140101629.
3
AmI and deployment considerations in AAL services provision for elderly independent living: the MonAMI project.为独立生活的老年人提供 AAL 服务中的自我管理和部署问题考虑:MonAMI 项目。
Non-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older People.
非侵入式现实生活中的环境智能:处理嘈杂模式以帮助老年人。
Sensors (Basel). 2019 Jul 14;19(14):3113. doi: 10.3390/s19143113.
Sensors (Basel). 2013 Jul 12;13(7):8950-76. doi: 10.3390/s130708950.
4
A review of wearable sensors and systems with application in rehabilitation.可穿戴传感器及系统综述及其在康复中的应用。
J Neuroeng Rehabil. 2012 Apr 20;9:21. doi: 10.1186/1743-0003-9-21.
5
Biomechanical energy harvesting from human motion: theory, state of the art, design guidelines, and future directions.从人体运动中获取生物力学能量:理论、现状、设计指南和未来方向。
J Neuroeng Rehabil. 2011 Apr 26;8:22. doi: 10.1186/1743-0003-8-22.
6
Inability to get up after falling, subsequent time on floor, and summoning help: prospective cohort study in people over 90.跌倒后无法起身、随后在地上停留的时间以及呼救情况:针对90岁以上人群的前瞻性队列研究
BMJ. 2008 Nov 17;337:a2227. doi: 10.1136/bmj.a2227.
7
Respiratory rate: the neglected vital sign.呼吸频率:被忽视的生命体征。
Med J Aust. 2008 Jun 2;188(11):657-9. doi: 10.5694/j.1326-5377.2008.tb01825.x.
8
A review of smart homes- present state and future challenges.智能家居综述——现状与未来挑战
Comput Methods Programs Biomed. 2008 Jul;91(1):55-81. doi: 10.1016/j.cmpb.2008.02.001. Epub 2008 Mar 25.
9
Fall detection--principles and methods.跌倒检测——原理与方法
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:1663-6. doi: 10.1109/IEMBS.2007.4352627.
10
Monocular 3D head tracking to detect falls of elderly people.用于检测老年人跌倒的单目3D头部跟踪
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:6384-7. doi: 10.1109/IEMBS.2006.260829.