Collaborative Research: CT-ISG: Error-resistant, Accountable, RFID-assisted Wireless Sensor Networks for Elder Cardiac Tele-Healthcare

合作研究：CT-ISG：用于老年人心脏远程医疗保健的防错、可靠、RFID 辅助无线传感器网络

• 批准号: 0716211
• 负责人: Yang Xiao
• 金额: $ 18.08万
• 依托单位: University of Alabama Tuscaloosa
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0716211&HistoricalAwards=false
• 关键词: Collaborative; Research; CT; ISG; Error

Tele-healthcare could largely reduce national healthcare cost through remote self-managed patient monitoring. Cardiac Sensor Networks (CSNs) could be used to deploy such a system. Moreover, the integration of RFID into CSN could play an important role for elder healthcare because RFID could be used to monitor elders' medicine taking behaviors. On the other hand, the disclosure of RFID information during RFID tag-to-reader communications can cause the violation of patients' privacy. This research aims to achieve trustworthiness in a practical RFID-assisted CSN platform. This project will make the following three contributions: (1) Error-resistant ECG transmission: A trustworthy CSN should be able to overcome the impacts of radio interference and propagation distortions that can lead to frequent ECG transmission errors. This research will use the receiver-only local ECG processing to overcome ECG errors/loss. It will conduct a comparative study of two promising anti-interference methods, Kalman Filter and Tempo-spatial Regression. (2) Low-overhead RFID security: This research will design a lightweight RFID security scheme based on Linear Congruential Generator (LCG) and a mutual authentication scheme. The RFID security will be tested in our current CSN hardware platform. (3) CSN temporal accountability: In ECG sensor applications, all ECG anomaly detections depend on accountable time interval analysis between different ECG signal segments. This research will achieve CSN temporal accountability through the following two technical approaches: i) design a receiver-only clock uncertainty prediction model to avoid wireless communication overhead; and ii) design a history-aware, reputation based trust model to capture the evolutionary timing attacks.

远程医疗可以通过远程自我管理的患者监测来大大降低国家医疗成本。心脏传感器网络（CSN）可以用于部署这样的系统。此外，将RFID集成到CSN中可以为老年人医疗保健发挥重要作用，因为RFID可以用于监测老年人的服药行为。另一方面，在RFID标签与阅读器通信期间RFID信息的泄露会导致对患者隐私的侵犯。本研究的目的是在一个实用的RFID辅助CSN平台实现可信。本项目将做出以下三个贡献：（1）抗错误的心电图传输：一个值得信赖的CSN应该能够克服无线电干扰和传播失真的影响，这些影响可能导致频繁的心电图传输错误。本研究将使用仅接收器本地ECG处理来克服ECG错误/丢失。对卡尔曼滤波和时空回归这两种有前途的抗干扰方法进行了比较研究。(2)低开销RFID安全性：本研究将设计一个轻量级的基于线性同余发生器（LCG）的RFID安全方案和一个双向认证方案。RFID安全性将在我们目前的CSN硬件平台上进行测试。(3)CSN时间问责：在ECG传感器应用中，所有ECG异常检测都依赖于不同ECG信号段之间的可靠时间间隔分析。本研究将通过以下两种技术途径实现CSN时间可问责性：i）设计仅接收方时钟不确定性预测模型以避免无线通信开销;以及ii）设计历史感知的、基于信誉的信任模型以捕获进化定时攻击。