Complex surgical procedures in hospitals are increasingly aided by robotic surgery systems, often at the request of patients. These systems allow greatly increased precision, reach and flexibility to the surgeon. However, their powerful capabilities entail substantial system complexity in both hardware and software. The high probability of serious injuries should a malfunction occur calls for rigorous assessment and monitoring of the reliability and safety of these cyber-physical systems. In this research project, a framework for assessing and monitoring the reliability and safety of robotic surgery systems during development, field testing, and general deployment is being developed. The proposed framework complements existing techniques used in earlier phases of validation by taking into account how surgeons actually use a robotic surgery system, how it is affected by operating conditions, and how its observable behavior is related to its hardware and software dynamics. Before deployment, this framework uses accurate simulations to assess pre-clinical reliability. After deployment, the framework uses data collection through online monitoring of the system as it is being used in the field, followed by analysis to obtain assessments of operational reliability and safety. The collected data is also used to improve the simulations for future testing. The framework also aims to support post-market surveillance of these systems by providing a workable basis for reassessing reliability and safety properties after system maintenance. The developed tools and methods will also have applications in the validation of safety and reliability of other medical devices with embedded software and other cyber-physical systems in general.

The objective of this research is to develop a cyber-physical system capable of displaying the in vivo surgical area directly onto patients' skin in real-time high definition. This system will give surgeons an x-ray vision experience, since they see directly through the skin, and remove a spatial bottleneck and additional scarring caused by laparoscopes in minimally invasive surgery. The approach is to develop micro-cameras that: occupy no space required by surgical tools, produce no additional scarring to the patient, and transfer wireless high-definition video images. A virtual view generating system will project the panoramic videos from all cameras to the right spot on the patient?s body with geometry and color distortion compensation. A surgeon-camera-interaction system will be investigated to allow surgeons to control viewpoint with gesture recognition and finger tracking. Novel techniques will be developed for zero-latency high-definition wireless video transfer through the in vivo/ex vivo medium. Image viewpoint alignment and distortion compensation in real time will also be investigated. The results will be a potential paradigm shift in minimally invasive surgery. The proposed work benefits the millions of surgeries capable of being performed through a single incision in the abdomen by providing virtually transparent skin to surgeons who will enjoy all the visual benefits of open-cavity surgery without all the associated risks to the patient. The goals of this research are extremely hands-on and immediately applicable to outreach activities that can excite youth, minority students, and others about the science, medicine a and engineering careers.

The objective of this research is to develop algorithms and software for treatment planning in intensity modulated radiation therapy under assumption of tumor and healthy organs motion. The current approach to addressing tumor motion in radiation therapy is to treat it as a problem and not as a therapeutic opportunity. However, it is possible that during tumor and healthy organs motion the tumor is better exposed for treatment, allowing for the prescribed dose treatment of the tumor (target) while reducing the exposure of healthy organs to radiation. The approach is to treat tumor and healthy organs motion as an opportunity to improve the treatment outcome, rather than as an obstacle that needs to be overcome. Intellectual Merit: The leading intellectual merit of this proposal is to develop treatment planning and delivery algorithms for motion-optimized intensity modulated radiation therapy that exploit differential organ motion to provide a dose distribution that surpasses the static case. This work will show that the proposed motion-optimized IMRT treatment planning paradigm provides superior dose distributions when compared to current state-of-the art motion management protocols. Broader Impact: Successful completion of the project will mark a major step for clinical applications of intensity modulated radiation therapy and will help to improve the quality of life of many cancer patients. The results could be integrated within existing devices and could be used for training of students and practitioners. The visualization software for dose accumulation could be used to train medical students in radiation therapy treatment planning.

Body Area Sensor Networks: A Holistic Approach from Silicon to Users The objective of this research is to develop new principles and techniques for adaptive operation in highly dynamic physical environments, using miniaturized, energy-constrained devices. The approach is to use holistic cross-layer solutions that simultaneously address all aspects of the system, from low-level hardware design to higher-level communication and data fusion algorithms to top-level applications. In particular, this work focuses on body area sensor networks as emerging cyber-physical systems. The intellectual merit includes producing new principles regarding how cyber systems must be designed in order to continually adapt and respond to rapidly changing physical environments, sensed data, and application contexts in an energy-efficient manner. New cross-layer technologies will be created that use a holistic bottom-up and top-down design -- from silicon to user and back again. A novel system-on-a-chip hardware platform will be designed and fabricated using three cutting-edge technologies to reduce the cost of communication and computation by several orders of magnitude. The broad impact of this project will enable the wide range of applications and societal benefits promised by body area networks, including improving the quality and reducing the costs of healthcare. The technology will have broad implications for any cyber physical system that uses energy constrained wireless devices. A new seminar series will bring together experts from many fields (including domain experts, such as physicians and healthcare professionals). The key aspects of this work that deal with healthcare have the potential to attract women and minorities to the computer field.

The objective of this research is to integrate user control with automated reflexes in the human-machine interface. The approach, taking inspiration from biology, analyzes control-switching issues in brain-computer interfaces. A nonhuman primate will perform a manual task while movement- and touch-related brain signals are recorded. While a robotic hand replays the movements, electronic signals will be recorded from touch sensors on the robot?s fingers, then mapped to touch-based brain signals, and used to give the subject tactile sensation via direct cortical stimulation. Context-dependent transfers of authority between the subject and reflex-like controls will be developed based on relationships between sensor signals and command signals. Issues of mixed authority and context awareness have general applicability in human-machine systems. This research advances methods for providing tactile feedback from a remote manipulator, dividing control appropriate to human and machine capabilities, and transferring authority in a smooth, context-dependent manner. These principles are essential to any cyber-physical system requiring robustness in the face of uncertainty, control delays, or limited information flow. The resulting transformative methods of human-machine communication and control will have applications for robotics (space, underwater, military, rescue, surgery, assistive, prosthetic), haptics, biomechanics, and neuroscience. Underrepresented undergraduates will be recruited from competitive university programs at Arizona State University and Mexico's Tec de Monterrey University. Outreach projects will engage the public and underrepresented school-aged children through interactive lab tours, instructional modules, and public lectures on robotics, human-machine systems, and social and ethical implications of neuroprostheses.

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.

The goal of this project is to develop a novel cyber-physical system (CPS) for performing multimodal image-guided robot-assisted minimally invasive surgeries (MIS). The approach is based on: (1) novel quantitative analysis of multi-contrast data, (2) control that uses this information to maneuver conformable robotic manipulators, while adjusting on-the-fly scanning parameters to acquire additional information, and (3) human-information/machine-interfacing for comprehensive appreciation of the physical environment. The intellectual merit arises from the development of: (1) a CPS that relies on "real" and "real-time" data, minimizing parametric and abstracted assumptions, extracts and matures information from a dynamic physical system (patient and robot) by combining management of data collection (at the physical sensor site) and data analysis (at the cyber site), (2) "smart sensing", to control data acquisition based on disruptive or situation altering events, (3) control coordination by interlacing sensing, control and perception, and the incorporation of steerable tools. The societal impact arises from contributions to a leap in MIS: from "keyhole" visualization (i.e., laparoscopy) to in-situ real-time image guidance, thereby enabling a wider range of MIS. This will directly benefit patients and their families (faster recovery/reduced trauma). Economic impact arises from the cost-effectiveness of MIS to the health care system, faster patient return to the workplace, and technology commercialization. The project will integrate research and education, diversity and outreach, by enhancing current and introducing new research-intensive courses in Cyber-physical Systems, Medical Imaging and Medical Robotics, and dissemination via trans-institutional collaborations, a comprehensive web site, multimedia web-seminars, and distribution to high schools.

The objective of this research is to develop an intuitive user interface for functional electrical stimulation (FES), which uses surgically-implanted electrodes to stimulate muscles in spinal cord-injured (SCI) patients. The challenge is to enable high-level tetraplegic patients to regain the use of their own arm. The approach is to develop a multi-modal Bayesian user-intent decoder; use natural muscle synergies to generate appropriate low-dimensional muscle activation signals in a feedforward controller; develop a feedback controller to enhance the performance of the feedforward controller; and test the system with SCI patients on daily living tasks, such as reaching, grasping, and eating. The challenge problem of restoring arm use to SCI patients will lead to new design principles for cyber-physical systems interfacing neural and biological systems with engineered computation and electrical power systems. The tight integration of the proposed user interface and controller with the users own control system requires a deep understanding of biological design principles such as nested feedback loops at different time and length scales, noisy signals, parallel processing, and highly coupled neuromechanical systems. This work will lead to new technology that dramatically improves the lives of spinal cord-injured patients. These patients often have no cognitive impairment and have long life spans after injury. The goal is to enable these patients to eat, reach, and grasp nearby objects. These tasks are critical for independent living and quality of life. This work will also help train a new generation of students in human-machine interfaces at the undergraduate, graduate, and postdoctoral levels.

The objective of this research is to understand mechanisms for generating natural movements of skeletal mechanisms driven by stochastically-controlled, biologically-inspired actuators. The approach is to verify the hypothesis that the variability associated with high redundancy and the stochastic nature of the actuation is key to generating natural movements. This project seeks to: (i) develop a method to model and characterize actuator array topologies; (ii) develop a method to analyze the force variability of stochastic actuator arrays; (iii) develop an analytical method to generate movements for a robot with multiple degrees of freedom by minimizing the effect of variability; and (iv) demonstrate the validity of the approach through the development of a robotic arm driven by multiple stochastic array actuators. With respect to intellectual merit, the study of inhomogeneous stochastic actuator network topologies inspired by neuromuscular systems could find the "missing links" that bridge the gap between biological natural movements and the ones in artificial systems. Potential results could impact other research areas, including robust computer networks, robust immune systems, and redundant muscle coordination. With respect to broader impacts, a new graduate-level course provides students in engineering and science with a comprehensive and multidisciplinary education in the underlying principles, cutting-edge applications, and societal impacts of biologically-inspired robotics. Outreach activities include an interactive educational program for K-12 students and a workshop for high-school students and their mentors on robot development. International collaboration with Tokyo University of Science, Japan, will be initiated.

Objectives and approaches. The objective of this research is to create a novel Cyber-Physical System, a self-reconfiguring ?second skin orthotic sleeve? consisting of programmable materials. The orthotic sleeve, worn over one or more limbs of brain-injured individuals, may restore brain function by promoting enriched exploration of self-produced limb movements. The approach consists of three steps (1) micro-fabricating sheets with embedded sensors and muscle-like collections of force-producing actuators, (2) conducting longitudinal recordings of kicking by typically developing and preterm brain-injured infants who wear a sensing, but not actuated micro-fabricated second skin, and (3) developing biologically-inspired programming techniques to help determine an algorithm with which the second skin embedded actuators may adaptively assist the ever-changing developmental pattern of infant kicking. The technology can be applied to many mobility-impaired populations,including children and adults with brain injury, the ageing population, and injured soldiers. The project will inform basic scientific and engineering research in areas such as formation of architectural structures by large-scale multi-agent robotic systems, and self-organization of swarming small-scale agents that act autonomously in cooperation with biological systems. The multi-institutional effort of this research endeavor will positively impact undergraduate and graduate science education via explorations of the intersection of biology and computation in cyber-physical systems. Innovation, teamwork, and the value of communication are encouraged. These efforts will promote education of an American work force that is technically expert, scientifically comprehensive, and socially aware to sustain national excellence in a future increasingly based on technologically complex systems.