Abstract: With nearly 10 million individuals carrying a diagnosis of Parkinson’s disease across the globe. Individuals with Parkinson’s disease experience tremors, rigidity, slowness of movement, and difficulties with walking and driving. Currently these individuals are required to attend weekly visits to the doctor's office for consistent reassessment regarding progression of the disease.

In pursuit of the long-term goal of enabling interpretable “white-box” autonomy in healthcare, the goal of this project is to investigate physiological modeling, coordinated and resilient multivariable closed-loop control, and regulatory science methodologies for white-box autonomy, as well as to illustrate its application to an important critical care scenario of circulatory resuscitation.  The idea of introducing autonomy to the healthcare domain is not new.  However, prior autonomy capabilities have not been suitably mature for real-world critical care, due to the limitations a

Computer modeling and simulation for medical device evaluation has been pursued as a means for reducing the cost and scope of clinical trials while minimizing the risk of unforeseen adverse outcomes. Advances in computational technologies and algorithms have further enabled analysis with complex and realistic Bayesian models to be applied to clinical trials.

Abstract: This project develops an integrated design and simulation environment for the creation of miniature capsule robots (MCRs). An MCR is a biocompatible Cyber-Physical System (CPS) designed to operate in the human body to accomplish diagnostic or therapeutic tasks (e.g., colonoscopy, abdominal surgery, etc.). A typical MCR has to fulfill three main constraints: safety, low power operation and small size. Advances in miniaturization of electronic devices have made MCRs a reality.

The problem of controlling biomechatronic systems, such as multiarticulating prosthetic hands, involves unique challenges in the science and engineering of Cyber Physical Systems (CPS), requiring integration between computational systems for recognizing human functional activity and intent and controlling prosthetic devices to interact with the physical world. Research on this problem has  been limited by the difficulties in noninvasively acquiring robust biosignals that allow intuitive and reliable control of multiple degrees of freedom (DoF).

Special Interest Group: Medical Devices, Discussion Lead: Oleg Sokolsky (U Penn), This session brings together CPS researchers who work on topics related to health care.  The goal of the session is to seek a common vision for the field and pursue a coordinated agenda of Medical CPS (MCPS) research. Possible agenda items:

Notes from the BoF Session on Medical CPS at the 2011 NSF CPS PI meeting.