Collaborative Research: Multi-Scale QoS for Body Sensor Networks

协作研究:身体传感器网络的多尺度 QoS

基本信息

  • 批准号:
    0901686
  • 负责人:
  • 金额:
    $ 35万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2009
  • 资助国家:
    美国
  • 起止时间:
    2009-08-01 至 2013-07-31
  • 项目状态:
    已结题

项目摘要

The objective of this collaborative research project is to address the key quality of service (QoS) issues related to wireless body sensor networks (BSNs) to make them practical and efficacious for continuous, non-invasive monitoring of individuals in a variety of healthcare applications. The approach is to develop new system modeling and analysis techniques for design-time optimization and run-time management of application fidelity, network latency and throughput, and energy. The key feature of this project is the multi-scale approach to QoS, enabling designers to explore how techniques at each system level impact the other levels. This work will be validated and improved upon based on experimentation with physical BSN systems deployed in real BSN applications.With respect to intellectual merit, this research address the problem of achieving high levels of QoS under severe resource constraints, in complex environments, and with varying application semantics and contexts. While a layered approach to QoS management is appropriate for resource-heavy systems, BSNs require an integrated, multi-scale approach capable of finding operating points across system levels to maximize QoS metrics based on application-specific requirements and dynamic operating conditions.With respect to broader impact, the QoS issues addressed in this research are central to the ultimate acceptance of BSNs in the healthcare applications for which they have such promise. This project includes interactions with doctors and nurses to ensure that BSNs are addressing the requirements of real applications, including deployment in home healthcare and assisted living settings. The project also seeks to get young students excited about engineering through hands-on demonstrations and clear links to compelling applications.
该合作研究项目的目标是解决与无线身体传感器网络(BSNs)相关的关键服务质量(QoS)问题,使其在各种医疗保健应用中对个人进行连续、非侵入性监测时切实有效。该方法是开发新的系统建模和分析技术,用于设计时优化和运行时管理应用程序保真度、网络延迟和吞吐量以及能量。该项目的关键特征是QoS的多尺度方法,使设计人员能够探索每个系统级别的技术如何影响其他级别。这项工作将在实际BSN应用中部署物理BSN系统的实验基础上进行验证和改进。关于智力价值,本研究解决了在严重资源约束下,在复杂环境中,以及在不同的应用语义和上下文中实现高水平QoS的问题。虽然QoS管理的分层方法适用于资源繁重的系统,但bsn需要一种集成的、多尺度的方法,能够找到跨系统级别的操作点,从而根据特定应用程序的需求和动态操作条件最大化QoS指标。就更广泛的影响而言,本研究中解决的QoS问题对于BSNs在医疗保健应用程序中的最终接受至关重要,因为它们有这样的承诺。该项目包括与医生和护士的互动,以确保BSNs满足实际应用的需求,包括在家庭保健和辅助生活环境中的部署。该项目还试图通过实际演示和引人注目的应用程序的清晰链接,让年轻学生对工程感兴趣。

项目成果

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John Lach其他文献

Making Meaning of “Messy” Data: Creating Clinically Useful Visualizations to Represent the Experience of Cancer Pain in the Home Setting (GP732)
  • DOI:
    10.1016/j.jpainsymman.2022.04.123
  • 发表时间:
    2022-06-01
  • 期刊:
  • 影响因子:
  • 作者:
    Virginia LeBaron;Nutta Homdee;Nyota Patel;Rachel Bennett;Nadim El-Jaroudi;Yudel Martinez Salgado;Emmanuel Ogunjirin;John Lach
  • 通讯作者:
    John Lach
Alloyed Branch History: Combining Global and Local Branch History for Robust Performance
Understanding the Experience of Cancer Pain From the Perspective of Patients and Family Caregivers to Inform Design of an In-Home Smart Health System: Multimethod Approach (Preprint)
从患者和家庭护理人员的角度了解癌症疼痛的经历,为家庭智能医疗系统的设计提供信息:多方法方法(预印本)
  • DOI:
    10.2196/preprints.20836
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    13.6
  • 作者:
    Virginia T. LeBaron;Rachel Bennett;Ridwan Alam;L. Blackhall;Kate Gordon;J. Hayes;Nutta Homdee;Randy Jones;Yudel Martinez;Emmanuel Ogunjirin;Tanya Thomas;John Lach
  • 通讯作者:
    John Lach
Automatic, wearable-based, in-field eating detection approaches for public health research: a scoping review
用于公共卫生研究的基于可穿戴设备的自动现场进食检测方法:范围审查
  • DOI:
    10.1038/s41746-020-0246-2
  • 发表时间:
    2020-03-13
  • 期刊:
  • 影响因子:
    15.100
  • 作者:
    Brooke M. Bell;Ridwan Alam;Nabil Alshurafa;Edison Thomaz;Abu S. Mondol;Kayla de la Haye;John A. Stankovic;John Lach;Donna Spruijt-Metz
  • 通讯作者:
    Donna Spruijt-Metz

John Lach的其他文献

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{{ truncateString('John Lach', 18)}}的其他基金

2018 Connections in Smart Health Workshop
2018智慧健康连线工作坊
  • 批准号:
    1841671
  • 财政年份:
    2018
  • 资助金额:
    $ 35万
  • 项目类别:
    Standard Grant
REU Site: Wireless Technologies for Health Applications
REU 网站:健康应用无线技术
  • 批准号:
    1461162
  • 财政年份:
    2015
  • 资助金额:
    $ 35万
  • 项目类别:
    Standard Grant
Safety Analysis of Body Sensor Networks
人体传感器网络的安全分析
  • 批准号:
    1240454
  • 财政年份:
    2012
  • 资助金额:
    $ 35万
  • 项目类别:
    Standard Grant
SHB: Medium: Collaborative Research: Non-Intrusive Multi-Patient Fall-Risk Monitoring in Health Care Facilities
SHB:中:协作研究:医疗保健机构中的非侵入式多患者跌倒风险监测
  • 批准号:
    1065262
  • 财政年份:
    2011
  • 资助金额:
    $ 35万
  • 项目类别:
    Standard Grant
Enhancing AFO Efficacy through Continuous, Non-Invasive Gait Assessment
通过连续、非侵入性步态评估提高 AFO 功效
  • 批准号:
    1034071
  • 财政年份:
    2010
  • 资助金额:
    $ 35万
  • 项目类别:
    Standard Grant
CI-P: Development of Community Infrastructure for Body Sensor Network Research, Education, and Support
CI-P:身体传感器网络研究、教育和支持的社区基础设施开发
  • 批准号:
    0855197
  • 财政年份:
    2009
  • 资助金额:
    $ 35万
  • 项目类别:
    Standard Grant
Collaborative Research: Continuous, Non-Invasive Gait Analysis and Fall-Risk Assessment
合作研究:连续、非侵入性步态分析和跌倒风险评估
  • 批准号:
    0756645
  • 财政年份:
    2008
  • 资助金额:
    $ 35万
  • 项目类别:
    Standard Grant
Collaborative Research: CT-T: Manufacturing Variability-based Hardware Protection Techniques
合作研究:CT-T:基于制造变异性的硬件保护技术
  • 批准号:
    0716443
  • 财政年份:
    2007
  • 资助金额:
    $ 35万
  • 项目类别:
    Standard Grant
SEI: Hierarchical Dependency Graphs for Col-Space Design with Application to Leukocyte Detection and Tracking
SEI:Col 空间设计的分层依赖图及其在白细胞检测和跟踪中的应用
  • 批准号:
    0612049
  • 财政年份:
    2006
  • 资助金额:
    $ 35万
  • 项目类别:
    Continuing Grant
EHS: Highly Flexible Multi-Mode Embedded Systems
EHS:高度灵活的多模式嵌入式系统
  • 批准号:
    0410526
  • 财政年份:
    2004
  • 资助金额:
    $ 35万
  • 项目类别:
    Continuing Grant

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