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.

远程医疗保健可以通过远程自我管理的患者监控来很大程度上降低国家医疗保健成本。心脏传感器网络（CSN）可用于部署这样的系统。此外，将RFID集成到CSN中可以在老年人医疗保健中发挥重要作用，因为RFID可以用来监控老年人的服药行为。另一方面，RFID标签与阅读器通信过程中RFID信息的泄露可能导致侵犯患者隐私。本研究旨在在实用的 RFID 辅助 CSN 平台中实现可信性。该项目将做出以下三个贡献：（1）防错心电图传输：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的本地心电图处理来克服心电图错误/丢失。它将对卡尔曼滤波器和时空回归这两种有前途的抗干扰方法进行比较研究。 (2)低开销RFID安全：本研究将设计一种基于线性同余发生器(LCG)和相互认证方案的轻量级RFID安全方案。 RFID安全性将在我们当前的CSN硬件平台上进行测试。 (3) CSN 时间责任：在 ECG 传感器应用中，所有 ECG 异常检测都依赖于不同 ECG 信号段之间的责任时间间隔分析。本研究将通过以下两种技术途径实现CSN时间问责：i）设计仅接收器的时钟不确定性预测模型，以避免无线通信开销； ii) 设计一个历史感知、基于信誉的信任模型来捕获进化定时攻击。