The objective of this research is to investigate the foundations, methodologies, algorithms and implementations of cyberphysical networks in the context of medical applications. The approach is to design, implement and study Carenet, a medical care network, by investigating three critical issues in the design and construction of cyberphysical networks: (1) rare event detection and multidimensional analysis in cyberphysical data streams, (2) reliable and trusted data analysis with cyberphysical networks, including veracity analysis for object consolidation and redundancy elimination, entity resolution and information integration, and feedback interaction between cyber- and physical- networks, and (3) spatiotemporal data analysis including spatiotemporal cluster analysis, sequential pattern mining, and evolution of cyberphysical networks. Intellectual merit: This project focuses on several most pressing issues in large-scale cyberphysical networks, and develops foundations, principles, methods, and technologies of cyberphysical networks. It will deepen our understanding of the foundations, develop effective and scalable methods for mining such networks, enrich our understanding of cyberphysical systems, and benefit many mission-critical applications. The study will enrich the principles and technologies of both cyberphysical systems and information network mining. Broader impacts: The project will integrate multiple disciplines, including networked cyberphysical systems, data mining, and information network technology, and advance these frontiers. It will turn raw data into useful knowledge and facilitate strategically important applications, including the analysis of patient networks, combat networks, and traffic networks. Moreover, the project systematically generates new knowledge and contains a comprehensive education and training plan to promote diversity, publicity, and outreach.

The objective of this research is to investigate the foundations, methodologies, algorithms and implementations of cyberphysical networks in the context of medical applications. The approach is to design, implement and study Carenet, a medical care network, by investigating three critical issues in the design and construction of cyberphysical networks: (1) rare event detection and multidimensional analysis in cyberphysical data streams, (2) reliable and trusted data analysis with cyberphysical networks, including veracity analysis for object consolidation and redundancy elimination, entity resolution and information integration, and feedback interaction between cyber- and physical- networks, and (3) spatiotemporal data analysis including spatiotemporal cluster analysis, sequential pattern mining, and evolution of cyberphysical networks. Intellectual merit: This project focuses on several most pressing issues in large-scale cyberphysical networks, and develops foundations, principles, methods, and technologies of cyberphysical networks. It will deepen our understanding of the foundations, develop effective and scalable methods for mining such networks, enrich our understanding of cyberphysical systems, and benefit many mission-critical applications. The study will enrich the principles and technologies of both cyberphysical systems and information network mining. Broader impacts: The project will integrate multiple disciplines, including networked cyberphysical systems, data mining, and information network technology, and advance these frontiers. It will turn raw data into useful knowledge and facilitate strategically important applications, including the analysis of patient networks, combat networks, and traffic networks. Moreover, the project systematically generates new knowledge and contains a comprehensive education and training plan to promote diversity, publicity, and outreach.

The objective of this research is to create interfaces that enable people with impaired sensory-motor function to control interactive cyber-physical systems such as artificial limbs, wheelchairs, automobiles, and aircraft. The approach is based on the premise that performance can be significantly enhanced merely by warping the perceptual feedback provided to the human user. A systematic way to design this feedback will be developed by addressing a number of underlying mathematical and computational challenges. The intellectual merit lies in the way that perceptual feedback is constructed. Local performance criteria like stability and collision avoidance are encoded by potential functions, and gradients of these functions are used to warp the display. Global performance criteria like optimal navigation are encoded by conditional probabilities on a language of motion primitives, and metric embeddings of these probabilities are used to warp the display. Together, these two types of feedback facilitate improved safety and performance while still allowing the user to retain full control over the system. If successful, this research could improve the lives of people suffering from debilitating physical conditions such as amputation or stroke and also could protect people like drivers or pilots that are impaired by transient conditions such as fatigue, boredom, or substance abuse. Undergraduate and graduate engineering students will benefit through involvement in research projects, and K-12 students and teachers will benefit through participation in exhibits presented at the Engineering Open House, an event hosted annually by the College of Engineering at the University of Illinois.

The objective of this research is to develop new principles for creating and comparing models of skilled human activities, and to apply those models to systems for teaching, training and assistance of humans performing these activities. The models investigated will include both hybrid systems and language-based models. The research will focus on modeling surgical manipulations during robotic minimally invasive surgery. Models for expert performance of surgical tasks will be derived from recorded motion and video data. Student data will be compared with these expert models, and both physical guidance and information display methods will be developed to provide feedback to the student based on the expert model. The intellectual merit of this work lies in the development of a new set of mathematical tools for modeling human skilled activity. These tools will provide new insights into the relationship between skill, style, and content in human motion. Additional intellectual merit lies in the connection of hybrid systems modeling to language models, the creation of techniques for automated training, and in the assessment of new training methods. The broader impact of this research will be the creation of automated methods for modeling and teaching skilled human motion. These methods will have enormous implications for the training and re-training of the US workforce. This project will also impact many diversity and outreach activities, including REU programs and summer camps for K-12 outreach. The senior personnel of this project also participate in the Robotic Systems Challenge and the Women in Science and Engineering program.

The objective of this research is to develop an integrated methodology for control system design in situations where disturbances primarily result from routine human behavior, as, for example, in future artificial pancreas systems where meals and exercise are the main disturbances affecting blood glucose concentration. The approach is to recognize that human behavioral disturbances (i) are generally random but cannot be treated as zero-mean white noise processes and (ii) occur with statistical regularity but cannot be treated as periodic due to natural variation in human behavior. This emerging class of problems requires (i) the derivation of new mathematical representations of disturbances for specific applications and (ii) the formulation of new stochastic control models and algorithms that exploit statistical regularity in the disturbance process. The intellectual merit of the proposed research stems from the fact that it explicitly recognizes a new class of disturbances, human behavioral disturbances, seeking to develop an integrated approach to statistically characterizing and responding to future perturbations, adapting gracefully to uncertainty about the future. The anticipated research outcomes will be relevant in diverse fields, including stochastic hybrid control and human automation interaction. As a broader implication, the proposed research will enable the design of future field deployable artificial pancreas systems, potentially improving the lives of 1.5 million Americans suffering from Type 1 diabetes. With help from the two graduate students funded by the project, the principle investigator will supervise a Capstone design course, exposing undergraduates to various aspects of control under human behavioral disturbances.

The objective of this research is to create computational foundation, methods, and tools for efficient and autonomous optical micromanipulation using microsphere ensembles as grippers. The envisioned system will utilize a holographic optical tweezer, which uses multiple focused optical traps to position microspheres in three-dimensional space. The proposed approach will focus on the following areas. First, it will provide an experimentally validated optical-tweezers based workstation for concurrent manipulation of multiple cells. Second, it will provide algorithms for on-line monitoring of workspace to support autonomous manipulation. Finally, it will provide real-time image-guided motion planning strategies for transporting microspheres ensembles. The proposed work will lead to a new way of autonomously manipulating difficult-to-trap or sensitive objects using microspheres ensembles as reconfigurable grippers. The proposed work will also lead to fundamental advances in several cyber physical systems areas by providing new approaches to micromanipulations, fast and accurate algorithms with known uncertainty bounds for on-line monitoring of moving microscale objects, and real-time motion planning algorithms to transport particle ensembles. The ability to quickly and accurately manipulate individual cells with minimal training will enable researchers to conduct basic research at the cellular scale. Control over cell-cell interactions will enable unprecedented insights into cell signaling pathways and open up new avenues for medical diagnosis and treatment. The proposed integration of research with education will train students with a strong background in emerging robotics technologies and the inner workings of cells. These students will be in a unique position to rapidly develop and deploy specialized robotics technologies.

This proposed CPS project aims to enable intelligent telesurgery in which a surgeon, or a distributed team of surgeons, can work on tiny regions in the body with minimal access. The University of Washington will expand an existing open surgical robot testbed, and create a robust infrastructure for cyber-physical systems with which to extend traditional real-time control and teleoperation concepts by adding three new interfaces to the system: networking, intelligent robotics, and novel non-linear controllers. Intellectual Merit: This project aims to break new ground beyond teleoperation by adding advanced robotic functions. Equally robust and flexible networking, high-level interfaces, and novel controllers will be added to the existing sytsem. The resulting system will be an open architecture and a substrate upon which many cyber-physical system ideas and algorithms will be tested under realistic conditions. The platforms proven physical robustness will permit rigorous evaluation of results and the open interfaces will encourage collaboration and sharing of results. Broader Impacts: We expect the results to enable new research in multiple ways. First, the collaborators such as Johns Hopkins, U.C. Santa Cruz, and several foreign institutions will be able to remotely connect to new high level interfaces provided by this project. Second, for the first time a robust and completely open surgical telerobot will be available for research so that CPS researchers do not need to be limited to isolated toy problems but instead be able to prototype advanced surgical robotics techniques and evaluate them in realistic contexts including animal procedures.

The objective of this research is to develop a framework for the development and deployment of next-generation medical systems consisting of integrated and cooperating medical devices. The approach is to design and implement an open-source medical device coordination framework and a model-based component oriented programming methodology for the device coordination, supported by a formal framework for reasoning about device behaviors and clinical workflows. The intellectual merit of the project lies in the formal foundations of the framework that will enable rapid development, verification, and certification of medical systems and their device components, as well as the clinical scenarios they implement. The model-based approach will supply evidence for the regulatory approval process, while run-time monitoring components embedded into the system will enable "black box" recording capabilities for the forensic analysis of system failures. The open-source distribution of tools supporting the framework will enhance its adoption and technology transfer. A rigorous framework for integrating and coordinating multiple medical devices will enhance the implementation of complicated clinical scenarios and reduce medical errors in the cases that involve such scenarios. Furthermore, it will speed up and simplify the process of regulatory approval for coordination-enabled medical devices, while the formal reasoning framework will improve the confidence in the design process and in the approval decisions. Overall, the framework will help reduce costs and improve the quality of the health care.