
NSF Org: |
CNS Division Of Computer and Network Systems |
Recipient: |
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Initial Amendment Date: | September 9, 2014 |
Latest Amendment Date: | March 3, 2017 |
Award Number: | 1446900 |
Award Instrument: | Standard Grant |
Program Manager: |
Anindya Banerjee
abanerje@nsf.gov (703)292-7885 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
Start Date: | October 1, 2014 |
End Date: | September 30, 2018 (Estimated) |
Total Intended Award Amount: | $615,404.00 |
Total Awarded Amount to Date: | $615,404.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
3100 MARINE ST Boulder CO US 80309-0001 (303)492-6221 |
Sponsor Congressional District: |
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Primary Place of Performance: |
University of Colorado Boulder Boulder CO US 80309-0430 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | CPS-Cyber-Physical Systems |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.070 |
ABSTRACT
Title: CPS:Synergy:Collaborative Research: In-Silico Functional Verification of Artificial Pancreas Control Algorithms.
The project investigates a formal verification framework for artificial pancreas (AP) controllers that automate the delivery of insulin to patients with type-1 diabetes (T1D). AP controllers are safety critical: excessive insulin delivery can lead to serious, potentially fatal, consequences. The verification framework under development allows designers of AP controllers to check that their control algorithms will operate safely and reliably against large disturbances that include patient meals, physical activities, and sensor anomalies including noise, delays, and sensor attenuation. The intellectual merits of the project lie in the development of state-of-the-art formal verification tools, that reason over mathematical models of the closed-loop including external disturbances and insulin-glucose response. These tools perform an exhaustive exploration of the closed loop system behaviors, generating potentially adverse situations for the control algorithm under verification. In addition, automatic techniques are being investigated to help AP designers improve the control algorithm by tuning controller parameters to eliminate harmful behaviors and optimize performance. The broader significance and importance of the project are to minimize the manual testing effort for AP controllers, integrate formal tools in the certification process, and ultimately ensure the availability of safe and reliable devices to patients with type-1 diabetes. The framework is made available to researchers who are developing AP controllers to help them verify and iteratively improve their designs. The team is integrating the research into the educational mission by designing hands-on courses to train undergraduate students in the science of Cyber-Physical Systems (CPS) using the design of AP controllers as a motivating example. Furthermore, educational material that explains the basic ideas, current challenges and promises of the AP concept is being made available to a wide audience that includes patients with T1D, their families, interested students, and researchers.
The research is being carried out collaboratively by teams of experts in formal verification for Cyber-Physical Systems, control system experts with experience designing AP controllers, mathematical modeling experts, and clinical experts who have clinically evaluated AP controllers. To enable the construction of the verification framework from the current state-of-the-art verification tools, the project is addressing major research challenges, including (a) building plausible mathematical models of disturbances from available clinical datasets characterizing human meals, activity patterns, and continuous glucose sensor anomalies. The resulting models are integrated in a formal verification framework; (b) simplifying existing models of insulin glucose response using smaller but more complex delay differential models; (c) automating the process of abstracting the controller implementation for the purposes of verification; (d) producing verification results that can be interpreted by control engineers and clinical researchers without necessarily understanding formal verification techniques; and (e) partially automating the process of design improvements to potentially eliminate severe faults and improve performance. The framework is evaluated on a set of promising AP controller designs that are currently under various stages of clinical evaluation.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The project studied the application of verfication approaches to artificial pancreas controllers in collabortion with engineers who develop the control system and clinicians who study the performance of these systems on patients. During the course of this project, we applied formal specification, verification and falsficiation approaches to a variety of control systems including PID, and rule-based controllers. Our initial work used ODE models of human physiology with parameter sets representing various patients. However, personalizing these models to individual patient physiology proved hard. In fact, human response to insulin and behavior around meals and physical activities are highly variable depending on age, gender, weight and height, among many other factors. We developed data-driven models and performed studies of controllers using these models.
The project contributed to collaborative educational outcomes that include a course on closed loop medical devices developed by PI Sankaranarayanan in collaboration with other PIs including Maahs, Cameron and Dr. Forlenza at the Barbara Davis Center, UC Denver Medical school. We also presented our work at numerous conferences and research seminars at various places including Stanford University, Barbara Davis Center for Type-1 Diabetes and
The key outcomes of this proposal include nearly 15 research papers including papers presented at diabetes conferences such as ATTD, journal paper in Diabetes Technology & Therapeutics, engineering conferences such as CPSWeek, and venues such as EMSOFT and IEEE RTSS. One MS thesis was published under this project and currently one PhD thesis in progress will owe partial support to this grant. Awards include a best paper nomination for EMSOFT 2017 and a best clinical poster award presented to PhD student Taisa Kushner at the Barbara Davis Center research symposium. Taisa's work won a place in the final at the "three minute thesis" competition organized by CU Boulder. The project involved undergraduate researchers including Alexandra Okeson, who won best poster award at the College of Engineering undergraduate research exposition.
Last Modified: 02/10/2019
Modified by: Sriram Sankaranarayanan
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