EAGER: Network Protocol Stack for Galvanic Coupled Intra-body Sensors

EAGER:电流耦合体内传感器的网络协议栈

基本信息

  • 批准号:
    1453384
  • 负责人:
  • 金额:
    $ 30万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-10-01 至 2018-09-30
  • 项目状态:
    已结题

项目摘要

Implanted sensors will enable the next generation of healthcare by in-situ testing of abnormal physiological conditions, personalized medicine and proactive drug delivery. These functions require energy efficient communication of data between implants through the body tissues, which is difficult to achieve via radio frequency (RF) waves owing to their high attenuation within the body. The project involves the design of a network protocol stack using weak electrical currents as the underlying communication mechanism, instead of conventional RF waves to connect the implants. This paradigm results in energy savings of two orders of magnitude compared to RF. This research will help in realizing diverse applications arising out from a network of connected implants that benefit athletes, military personnel, and other at-risk populations. The ability to proactively report physiological changes within the body will increase longevity of human life. The project incorporates outreach components targeting K-12 students, design of computer-simulation based projects, and demonstrations at public venues like science museums.The research planned in the course of this project is the first effort to systematically devise networking protocols based on galvanic coupling of electric signals. It has the following goals: (i) explore the impact of the transmission frequency and power on signal reflection and refraction at the tissue boundaries for multicast communication, (ii) design of interference-free medium access schemes that take into account heat generated at the crossings of the signal paths for all simultaneously active transceiver pairs, for both CSMA and TDMA-based approaches, (iii) research new strategies and conduct performance analysis for optimal placement of on-skin relay nodes for retrieving the sensor data from locations in the body that minimize the data gathering latency while being constrained by feasible on-body locations, and (iv) the first simulator and testbed for galvanic coupled communication using ns-3, and will also propose ways to charge the implanted sensors through contact-less magnetically coupled coils.
植入的传感器将通过原位检测异常生理状况、个性化医疗和主动给药,实现下一代医疗保健。这些功能需要通过身体组织在植入物之间进行高能效的数据通信,由于射频(RF)波在体内的高衰减,这很难通过射频波实现。该项目涉及网络协议栈的设计,使用弱电流作为底层通信机制,而不是传统的射频波来连接植入物。与射频相比,这种模式节省了两个数量级的能源。这项研究将有助于实现由连接的植入物网络产生的各种应用,使运动员、军事人员和其他高危人群受益。主动报告体内生理变化的能力将增加人类的寿命。该项目包括针对K-12学生的拓展部分,基于计算机模拟的项目设计,以及在科学博物馆等公共场所的演示。本项目计划的研究是第一次系统地设计基于电信号电耦合的网络协议。它有以下目标:(i)探索传输频率和功率对多播通信组织边界处信号反射和折射的影响;(ii)设计无干扰媒体接入方案,该方案考虑了所有同时有源的收发器对在信号路径交叉处产生的热量,适用于基于CSMA和tdma的方法;(iii)研究新的策略,并对皮肤上中继节点的最佳放置进行性能分析,以便在受可行的身体位置限制的情况下,从身体的位置检索传感器数据,最大限度地减少数据收集延迟;(iv)使用ns-3进行电偶通信的第一个模拟器和试验台,并将提出通过非接触磁耦合线圈对植入传感器充电的方法。

项目成果

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Kaushik Chowdhury其他文献

Kaushik Chowdhury的其他文献

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{{ truncateString('Kaushik Chowdhury', 18)}}的其他基金

NSF-SNSF: Rapid Beamforming for Massive MIMO using Machine Learning on RF-only and Multi-modal Sensor Data
NSF-SNSF:在纯射频和多模态传感器数据上使用机器学习实现大规模 MIMO 的快速波束成形
  • 批准号:
    2401047
  • 财政年份:
    2024
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
Collaborative Research: SWIFT: MEDUSA: Mid-band Environmental Sensing Capability for Detecting Incumbents during Spectrum Sharing
合作研究:SWIFT:MEDUSA:用于在频谱共享期间检测现有企业的中频环境传感能力
  • 批准号:
    2229444
  • 财政年份:
    2022
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
Collaborative Research: CCRI: New: RFDataFactory: Principled Dataset Generation, Sharing and Maintenance Tools for the Wireless Community
合作研究:CCRI:新:RFDataFactory:无线社区的原则性数据集生成、共享和维护工具
  • 批准号:
    2120447
  • 财政年份:
    2021
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
I-Corps: Smart Mask for Respiratory Monitoring and Prevention of Airborne Diseases
I-Corps:用于呼吸监测和预防空气传播疾病的智能口罩
  • 批准号:
    2042080
  • 财政年份:
    2021
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
SpecEES: DISCOVER: Device Identification for Spectrum-optimization using COnVolutional nEural netwoRks
SpecEES:DISCOVER:使用卷积神经网络进行频谱优化的设备识别
  • 批准号:
    1923789
  • 财政年份:
    2019
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
PFI:AIR-TT: DeepBeam: Wirelessly chargeable portable batteries through energy beamforming
PFI:AIR-TT:DeepBeam:通过能量波束成形进行无线充电的便携式电池
  • 批准号:
    1701041
  • 财政年份:
    2017
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
WiFiUS: Coordinating US-Finland Collaboration on Wireless Research through WiFiUS PI Meetings
WiFiUS:通过 WiFiUS PI 会议协调美国-芬兰无线研究合作
  • 批准号:
    1644763
  • 财政年份:
    2016
  • 资助金额:
    $ 30万
  • 项目类别:
    Continuing Grant
Student Travel Support for ACM MobiHoc 2016
ACM MobiHoc 2016 学生旅行支持
  • 批准号:
    1631979
  • 财政年份:
    2016
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
I-Corps: Software-Defined Distributed Wireless Charging
I-Corps:软件定义的分布式无线充电
  • 批准号:
    1644598
  • 财政年份:
    2016
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
CAREER: IDEA: Integrated Data and Energy Access for Wireless Sensor Networks
职业:IDEA:无线传感器网络的集成数据和能源访问
  • 批准号:
    1452628
  • 财政年份:
    2015
  • 资助金额:
    $ 30万
  • 项目类别:
    Continuing Grant

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