Skip directly to content

Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:UNIVERSITY OF ILLINOIS
Doing Business As Name:University of Illinois at Urbana-Champaign
PD/PI:
  • Ravishankar Iyer
  • (217) 333-9732
  • rkiyer@illinois.edu
Co-PD(s)/co-PI(s):
  • T. Kesavadas
  • Zbigniew Kalbarczyk
Award Date:02/05/2016
Estimated Total Award Amount: $ 500,000
Funds Obligated to Date: $ 500,000
  • FY 2016=$500,000
Start Date:02/15/2016
End Date:01/31/2019
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:CPS: Breakthrough:Towards Resiliency in Cyber-physical Systems for Robot-assisted Surgery
Federal Award ID Number:1545069
DUNS ID:041544081
Parent DUNS ID:041544081
Program:CPS-Cyber-Physical Systems
Program Officer:
  • David Corman
  • (703) 292-8754
  • dcorman@nsf.gov

Awardee Location

Street:1901 South First Street
City:Champaign
State:IL
ZIP:61820-7406
County:Champaign
Country:US
Awardee Cong. District:13

Primary Place of Performance

Organization Name:University of Illinois at Urbana-Champaign
Street:
City:
State:IL
ZIP:61820-7473
County:Champaign
Country:US
Cong. District:13

Abstract at Time of Award

Since 2000, surgical robots have been used in over 1.75 million minimally invasive procedures in the U.S. across various surgical specialties, including gynecological, urological, general, cardiothoracic, and head and neck surgery. Robotic surgical procedures promise decreased complication rates and morbidity, due to the minimally invasive nature of the procedures. A detailed analysis (also reported to the FDA) of the adverse events associated with the surgical robot indicates that despite the increased number of robotic procedures and their greater utilization, the rate of adverse events has remained relatively steady over the last 14 years. Even though current surgical robots are designed with safety mechanisms in mind, in practice several significant challenges exist in enabling timely and accurate detection and mitigation of adverse incidents during surgery. Toward this goal, the project will address (i) an in-depth analysis of incident causes, which takes into account the interactions among the system components, human operators, and patients; (ii) resiliency assessment of the robotic systems in the presence of realistic safety hazards, reliability failures, and malicious tampering; and (iii) continuous monitoring for detection of safety, reliability, and security violations to ensure patient safety. The intellectual merit of this work lies in: (i) systems-theoretic approach driven by real data on safety hazards and medical equipment recalls, to identify causes leading to violation of safety constraints at different layers of the cyber and physical system-control-structure; (ii) creation of a unique safety hazard simulation engine to perform injections into robot control software and emulate realistic safety hazard scenarios in a virtual environment; (iii) an adaptive method for rapid detection of events that lead to safety violations, based on continuous monitoring of human operator actions, robot state, and patient status, in conjunction with a probabilistic graph-model that captures dependencies between the causal factors leading to safety hazards; and (iv) experimental validation using the real robot to assess monitoring and protection mechanisms in the presence of realistic safety hazards, reliability faults, and security exploits (recreated using safety hazard simulation engine). The broader impact of the project is a methodology for design and resiliency assessment of a larger class of control cyber-physical systems, which involve humans in the on-line decision making loop. Application of the methodology to robot-assisted surgery demonstrates the strength and practicality of the approach and is likely to attract interest from areas of academia and industry in which cyber-physical systems are either a subject of study or the basis for delivering a service (e.g., transportation or electric power grids). This project's educational outreach encompasses strategies for broadening participation in multi-disciplinary projects spanning medicine and engineering.

Publications Produced as a Result of this Research

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

Xiao Li, Homa Alemzadeh, Daniel Chen, Zbigniew Kalbarczyk, Ravishankar K. Iyer "Surgeon Training in Telerobotic Surgery via a Hardware-in-the-Loop Simulator" Journal of Healthcare Engineering, v.2017, 2017, p.. doi:doi:10.1155/2017/6702919 

Subho S. Banerjee, Saurabh Jha, James Cyriac, Zbigniew T. Kalbarczyk and Ravishankar K. Iyer "Hands Off the Wheel in Autonomous Vehicles? A Systems Perspective on over a Million Miles of Field Data" IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), v., 2018, p..

Deka, Shankar A. and Li, Xiao and Stipanovic, D.M. and Kesavadas, Thenkurussi "Robust and Safe Coordination of Multiple Robotic Manipulators" Journal of Intelligent {\&} Robotic Systems, v., 2017, p.. doi:10.1007/s10846-017-0699-y 

Homa Alemzadeh, Daniel Chen, Xiao Li, Thenkurussi Kesavadas, Zbigniew Kalbarczyk, Ravishankar Iyer "Targeted Attacks on Teleoperated Surgical Robots: Dynamic Model-based Detection and Mitigation" International Conference on Dependable Systems and Networks, v., 2016, p..

Xiao Li, Homa Alemzadeh, Daniel Chen, Zbigniew Kalbarczyk, Ravishankar Iyer, Thenkurussi Kesavadas "A Hardware-in-the-loop Simulator for Safety Training in Robotic Surgery" International Conference on Intelligent Robots and Systems, v., 2016, p..

Hui Lin, Homa Alemzadeh, Daniel Chen, Zbigniew Kalbarczyk, Ravishankar Iyer "Safety-critical cyber-physical attacks: analysis, detection, and mitigation" Symposium and Bootcamp on the Science of Security, v., 2016, p..

Xiao Li, Homa Alemzadeh, Daniel Chen, Zbigniew Kalbarczyk, Ravishankar Iyer, Thenkurussi Kesavadas "Surgeon Training in Telerobotic Surgery via a Hardware-in-the-loop simulator" Journal of Healthcare Engineering, v., 2017, p..

Keywhan Chung, Zbigniew Kalbarczyk, Ravishankar Iyer "Availability Attacks on Computing Systems through Alteration of Environmental Control: Smart Malware Approach" International Conference on Cyber Physical Systems, v., 2019, p..

X. Li and T. Kesavadas "Surgical robot with environment reconstruction and force feedbac" International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), v., 2018, p..


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.

Despite significant improvements in the design of robotic surgical systems through the years, there are occurrences of safety incidents during procedures that negatively impact patients (e.g., major injuries or death). Our project focused on (i) understanding the causes and impacts of incidents that occur during robot-assisted surgical procedures, and (ii) transforming those insights into knowledge to drive development of tools and techniques for design and assessment of resilient surgical robots. We conducted an in-depth analysis of failure incidents and safety violations related to robot-assisted surgical procedure. Using a data-driven systematic approach, we created fault models that can recreate safety hazards during robotic surgical procedures. To enable assessment of the impact of safety hazards, we implemented a safety-hazard simulation engine (the preliminary version of the software was released under an open-source license) and custom-built fault injector that can replay safety hazards. Using the simulation engine, we characterized the resiliency of Raven-II surgical robot. We implemented a haptic rendering pipeline that accurately renders the force feedback during surgical procedures. We assessed the resiliency of the algorithm by using the simulation engine developed. The methodology developed in this project represents a compelling strategy for design and assessment of a broader class of control cyber-physical systems, which involve human in the on-line decision making loop.

 

We used the lessons learned and the tools developed to: (i) enhance graduate courses and undergraduate laboratories with topics on resilient cyber-physical systems; (ii) train undergraduate and graduate interns, (including underrepresented minorities and students from minority-serving institutions) on conducting research in CPS design and assessment; (iii) establish cross-departmental collaborations which was essential in delivering breakthroughs on design and assessment of resilient robotic systems, and (iv) provide insights on the common safety and security issues in robot-assisted surgical systems (and beyond) and on how to improve the resiliency of future systems. This research grant provided a partial support for three Ph.D. students.

Robotic surgical systems are among the most complex medical cyber-physical systems on the market. Despite significant improvements in the design of such systems through the years, there have been ongoing occurrences of safety incidents during procedures that negatively impact patients (e.g., major injuries or death). Even though state-of-the-art robotic surgical systems are designed with safety mechanisms that detect failures and attempt to put the system into a safe state, in practice, several significant challenges must still be addressed to enable timely and accurate detection, prediction, and mitigation of incidents during surgery.

Towards this, our project focused on (i) understanding the causes and impacts of incidents that occur during robot-assisted surgical procedures, and (ii) transforming those insights into knowledge to drive development of tools and techniques for design and assessment of resilient surgical robots. We conducted an in-depth analysis of failure incidents and safety violations related to robot-assisted surgical procedure. Using a data-driven systematic approach, we created real fault models that can recreate safety hazards during robotic surgical procedures. To enable assessment of the impact of safety hazards, we implemented a safety-hazard simulation engine and released the preliminary version of the software to the public with an open-source license. Our custom-built fault injector can replay safety hazards developed as part of the project. Using the simulation engine, we characterized the resiliency of Raven-II surgical robots. We implemented a haptic rendering pipeline that accurately renders the force feedback during surgical procedures. We assessed the resiliency of the algorithm (implemented as an application running on top of the robot operating system (ROS)) by using the simulation engine that allows us to exercise the algorithm under a several types of faults.

The methodology developed in this project represents a compelling strategy for design and assessment of a broader class of control cyber-physical systems, which involve human in the on-line decision making loop. Application of the methodology to robot-assisted surgery demonstrates the strength and practicality of the approach and applicability to other domains in which cyber-physical systems are the basis for delivering a service (e.g., transportation or electric power grids).

As part of the educational outreach we used the lessons learned and the tools developed (surgical robot simulator augmented with fault injection capabilities) to: (i) enhance graduate courses and undergraduate laboratories with topics on resilient cyber-physical systems; (ii) train undergraduate and graduate interns, (including underrepresented minorities and graduate students from minority-serving institutions) on conducting research in CPS design and assessment; (iii) establish cross-departmental collaborations which was essential in delivering breakthroughs on the design and assessment of resilient robotic systems, and (iv) provide industry with insights on the common safety and security issues in robot-assisted surgical systems (and beyond) and on how to improve the resiliency of future systems. This research grant has provided a partial support for three Ph.D. students whose work has been published and presented at international conferences and in scientific journals as summarized in the table attached as an image.


Last Modified: 06/14/2019
Modified by: Zbigniew Kalbarczyk

For specific questions or comments about this information including the NSF Project Outcomes Report, contact us.