Fault-tolerant Control Systems for Artificial Pancreas

描述(申请人提供)：最近对人工胰腺(AP)系统的研究产生了各种AP技术，在临床研究中表现良好，并表明需要提高患者日常使用AP的可靠性。通过集成多变量监测、故障检测和诊断、传感器冗余和容错控制技术，可以设计可靠和健壮的AP系统，以向用户和医疗保健提供者提供自我恢复、针对故障和警告的保护措施和消息。拟议的研究重点是开发一种容错AP，它集成了这些技术，降低了AP系统中的风险，并在BGC调节的可接受水平上发挥作用，直到诊断的故障能够被修复或能够安全地转移到用户手动操作的胰岛素泵。我们的研究重点是开发多变量算法和软件工具，用于性能监控、故障检测和诊断、控制系统性能评估、传感器的分析冗余、具有容错和恢复功能的控制算法，以及为用户和护理人员提供警报系统，以创建容错AP系统。我们方法的关键特征是使用生理变量信息来补充连续的血糖测量，多变量建模、监测、诊断和控制技术，以及递归模型和基于模型的自适应控制系统。还将开发具有多个输入(葡萄糖浓度和生理变量)的多变量模拟器，以测试性能监测、FDD、传感器冗余和容错控制模块，并评估容错AP系统的性能。将进行临床研究，以测试各模块和容错AP系统的性能。它们还将被用于评估AP使用中改善生活质量和减少对低血糖的恐惧的潜力。拟议的研究将由阿里·西纳-伊利诺伊理工学院、芝加哥伊丽莎白·利特尔约翰大学和伊利诺伊大学芝加哥分校劳里·奎因与美敦力公司和Body-Media，Inc.合作进行。

DESCRIPTION (provided by applicant): Recent research on artificial pancreas (AP) systems produced various AP technologies with good performance in clinical studies and indicated the need for improving the reliability of daily use of AP by patients. Reliable and robust AP systems can be designed by integrating multivariable monitoring, fault detection and diagnosis, sensor redundancy, and fault-tolerant control techniques to provide self-recovery, safeguards against failures and warnings and messages to users and medical care providers. The proposed research focuses on the development of a fault-tolerant AP that integrates these technologies, mitigates the risks in AP systems and functions at an acceptable level for BGC regulation until the diagnosed fault can be repaired or can provide safe transfer to manual operation of insulin pumps by the user. Our research focus is on the development of multivariable algorithms and software tools for performance monitoring, fault detection and diagnosis, control system performance assessment, analytical redundancy in sensors, control algorithms with fault-tolerance and recovery, and warning systems to users and care providers to a create fault-tolerant AP system. The critical characteristics of our approach are the use of physiological variable information to complement continuous glucose measurements, multivariable modeling, monitoring, diagnosis and control techniques, and recursive models and adaptive model-based control systems. A multivariable simulator with multiple inputs (glucose concentration and physiological variables) will also be developed to test the performance monitoring, FDD, sensor redundancy, and fault- tolerant control modules and assess the performance of fault-tolerant AP system. Clinical studies will be conducted to test the performance of various modules and of fault-tolerant AP system. They will also be used to assess the potential of quality of life improvements and reduction of fear of hypoglycemia in AP use. The proposed research will be collaboration between Ali Cinar - Illinois Institute of Technology, Elizabeth Littlejohn - Universiy of Chicago, and Laurie Quinn - University of Illinois at Chicago, in partnership with Medtronic Corporation and Body-Media, inc.