首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Wearable Sensors Integrated with Internet of Things for Advancing eHealth Care
【2h】

Wearable Sensors Integrated with Internet of Things for Advancing eHealth Care

机译:可穿戴式传感器与物联网集成促进电子医疗保健

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Health and sociological indicators alert that life expectancy is increasing, hence so are the years that patients have to live with chronic diseases and co-morbidities. With the advancement in ICT, new tools and paradigms are been explored to provide effective and efficient health care. Telemedicine and health sensors stand as indispensable tools for promoting patient engagement, self-management of diseases and assist doctors to remotely follow up patients. In this paper, we evaluate a rapid prototyping solution for information merging based on five health sensors and two low-cost ubiquitous computing components: Arduino and Raspberry Pi. Our study, which is entirely described with the purpose of reproducibility, aimed to evaluate the extent to which portable technologies are capable of integrating wearable sensors by comparing two deployment scenarios: Raspberry Pi 3 and Personal Computer. The integration is implemented using a choreography engine to transmit data from sensors to a display unit using web services and a simple communication protocol with two modes of data retrieval. Performance of the two set-ups is compared by means of the latency in the wearable data transmission and data loss. PC has a delay of 0.051 ± 0.0035 s (max = 0.2504 s), whereas the Raspberry Pi yields a delay of 0.0175 ± 0.149 s (max = 0.294 s) for N = 300. Our analysis confirms that portable devices (p    0.01) are suitable to support the transmission and analysis of biometric signals into scalable telemedicine systems.
机译:健康和社会学指标提醒人们,预期寿命在增加,因此患者必须患有慢性疾病和合并症的年龄也在增加。随着ICT的发展,人们正在探索新的工具和范例以提供有效和高效的医疗保健。远程医疗和健康传感器是促进患者参与,疾病自我管理并协助医生远程跟踪患者的必不可少的工具。在本文中,我们基于五个健康传感器和两个低成本无处不在的计算组件:Arduino和Raspberry Pi,评估了一种用于信息合并的快速原型解决方案。我们的研究完全以可再现性为目的进行了描述,旨在通过比较两种部署方案(Raspberry Pi 3和Personal Computer)来评估便携式技术能够集成可穿戴传感器的程度。集成使用编排引擎实现,以使用Web服务和具有两种数据检索模式的简单通信协议将数据从传感器传输到显示单元。通过可穿戴数据传输的延迟和数据丢失来比较这两个设置的性能。 PC的延迟为0.051±0.0035 s(最大= 0.2504 s),而Raspberry Pi对于N = 300的延迟为0.0175±0.149 s(最大= 0.294 s)。我们的分析证实了便携式设备(p <0.01 )适用于支持将生物特征信号传输和分析到可扩展的远程医疗系统中。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号