Motivated by the fact that the 2014 Ebola outbreak is the largest in history and there is a pressing need to understand how to improve delivery of care with the right technological interventions at the right place, this Rapid Response Research is aimed at realizing a human-in-the-loop medical cyber-physical system (CPS) for monitoring patients, insuring compliance with relevant safety protocols, and collecting data for advancing multidisciplinary research on infectious disease control. The ultimate goal is to enhance safety of Ebola workers by minimizing their contact with potentially contaminated surfaces and materials through integration of methods and technologies to realize smart and connected treatment clinics. This project could impact the response to infectious disease outbreaks by augmenting existing treatment clinics with cost-effective, modular, reconfigurable and
 open-design CPS technologies. The project will train a new cadre of engineering students, researchers and innovators to be 
sensitive to societal needs and national priorities by involving K-Gray, undergraduate and graduate students in all aspects of the project, especially at the co-ideation and co-design stages. The project will bring together a multidisciplinary team of engineers, scientists, technologists, medical experts, and humanitarian aid workers to develop holistic solutions to infectious disease control. The broader impacts also include operational cost savings in treatment clinics by reducing the need and use of the personal protective equipment and preserve resources such as water by reducing consumption. In order to prevent, detect and respond to current Ebola outbreak and future similar infectious disease outbreaks, this research plan has the following interconnected aims: (1) contribute new knowledge, methods, and tools to better understand the operational procedures in an infectious disease treatment clinic, (2) design, implement and validate a treatment ward augmented with a medical CPS for patient monitoring, (3) apply intuitive control interfaces and data visualization tools for practical human-robot interaction, (4) realize traded, coordinated and collaborative shared control techniques for safe and effective mobile robot navigation inside a treatment facility, (5) assess acceptability and effectiveness of the technology among health care workers and patients. The team will develop a self-contained, modular and reconfigurable system composed of a connected sensor network for patient monitoring and a mobile robot platform for telemedicine that will primarily focus on the interoperability and integration of existing standardized 
hardware and software systems to realize a testbed for verification and validation of a medical CPS. Medical, emergency response and humanitarian aid experts will be engaged to critically assess user-experiences and acceptability among medical staff to develop pathways for fielding the system in a treatment clinic. This RAPID project will lead the way in designing the next generation of human-in-the-loop medical CPS for empowering health care workers worldwide in treating patients during infectious disease outbreaks.

In the United States, there is still a great disparity in medical care and most profoundly for emergency care, where limited facilities and remote location play a central role. Based on the Wessels Living History Farm report, the doctor to patient ratio in the United States is 30 to 10,000 in large metropolitan areas, only 5 to 10,000 in most rural areas; and the highest death rates are often found in the most rural counties. For emergency patient care, time to definitive treatment is critical. However, deciding the most effective care for an acute patient requires knowledge and experience. Though medical best practice guidelines exist and are in hospital handbooks, they are often lengthy and difficult to apply clinically. The challenges are exaggerated for doctors in rural areas and emergency medical technicians (EMT) during patient transport. This project's solution to transform emergency care at rural hospitals is to use innovative CPS technologies to help hospitals to improve their adherence to medical best practice. The key to assist medical staff with different levels of experience and skills to adhere to medical best practice is to transform required processes described in medical texts to an executable, adaptive, and distributed medical best practice guidance (EMBG) system. Compared to the computerized sepsis best practice protocol, the EMBG system faces a much bigger challenge as it has to adapt the best practice across rural hospitals, ambulances and center hospitals with different levels of staff expertise and equipment capabilities. Using a Global Positioning System analogy, a GPS leads drivers with different route familiarity to their destination through an optimal route based on the drivers' preferences, the EMBG system leads medical personnel to follow the best medical guideline path to provide emergency care and minimize the time to definitive treatment for acute patients. The project makes the following contributions: 1) The codification of complex medical knowledge is an important advancement in knowledge capture and representation; 2) Pathophysiological model driven communication in high speed ambulance advances life critical communication technology; and 3) Reduced complexity software architectures designed for formal verification bridges the gap between formal method research and system engineering.

In the United States, there is still a great disparity in medical care and most profoundly for emergency care, where limited facilities and remote location play a central role. Based on the Wessels Living History Farm report, the doctor to patient ratio in the United States is 30 to 10,000 in large metropolitan areas, only 5 to 10,000 in most rural areas; and the highest death rates are often found in the most rural counties. For emergency patient care, time to definitive treatment is critical. However, deciding the most effective care for an acute patient requires knowledge and experience. Though medical best practice guidelines exist and are in hospital handbooks, they are often lengthy and difficult to apply clinically. The challenges are exaggerated for doctors in rural areas and emergency medical technicians (EMT) during patient transport. This project's solution to transform emergency care at rural hospitals is to use innovative CPS technologies to help hospitals to improve their adherence to medical best practice. The key to assist medical staff with different levels of experience and skills to adhere to medical best practice is to transform required processes described in medical texts to an executable, adaptive, and distributed medical best practice guidance (EMBG) system. Compared to the computerized sepsis best practice protocol, the EMBG system faces a much bigger challenge as it has to adapt the best practice across rural hospitals, ambulances and center hospitals with different levels of staff expertise and equipment capabilities. Using a Global Positioning System analogy, a GPS leads drivers with different route familiarity to their destination through an optimal route based on the drivers' preferences, the EMBG system leads medical personnel to follow the best medical guideline path to provide emergency care and minimize the time to definitive treatment for acute patients. The project makes the following contributions: 1) The codification of complex medical knowledge is an important advancement in knowledge capture and representation; 2) Pathophysiological model driven communication in high speed ambulance advances life critical communication technology; and 3) Reduced complexity software architectures designed for formal verification bridges the gap between formal method research and system engineering.