The artificial pancreas (AP) is a set of increasingly sophisticated devices and algorithms that will automate the delivery of insulin to patients with type-1 diabetes. While the AP concept promises to alleviate the burden posed by the self-management of blood glucose levels, it also poses significant risks arising from a combination of external disturbances such as patient meals, physical activity, sensor errors, network delays and physiological variations.

Our proposal’s main objective is to realize cyber-physical platform and principles for (i) interrogating global modalities of intracellular transport with causative factors isolated at the single-molecule scale and (ii) realizing efficient and robust infrastructure for transporting micron/molecular scale cargo using distributed strategies We are realizing in-vitro, a transport network with roadways formed by microtubules where motorproteins, kinesin and dynein, will form vehicles ferrying cargo.

Assistive machines, like robot arms mounted on powered wheelchairs, promote independence and ability in those with severe motor impairments. Users of these assistive robots can teleoperate their devices to perform activities of daily living like eating and self care. However, as these machines become more capable, they often also become more complex. Traditional teleoperation interfaces cover only a portion of the control space, and it is necessary to switch between di erent control modes to access the full control space.

The project is to develop an Executable Medical Best Practice Guidance (EMBG) system to assist the adherence of acute patient care at a rural hospital to the best medical practice as if the patient care is at a regional hospital. The EMBG system is adaptive to the changing needs of a patient and physical resource availability, just as a GPS-enabled navigation system can driver’s preference and accommodate road condition changes.

This project is a component of a larger effort is to develop the foundations of modeling, synthesis and development of verified medical device software and systems from verified closed-loop models of the device and organ(s). This research spans both implantable medical devices such as cardiac pacemakers and physiological control systems such as drug infusion pumps which have multiple networked medical systems. Here we focus on advancing two aspects of this work: (1) development of patient-specific models and therapies and (2) multi-scale modeling of complex physiological phenomena.

The CyberCardia project will lead to significant advances in the state of the art for system verification and cardiac therapies based on the use of formal methods and closed-loop control and verification.  The animating vision for the work is to enable the development of a true in silico design methodology for medical devices that can be used to speed the development of new devices and to provide greater assurance that their behavior matches designer intentions, and to pass regulatory muster more quickly so that they can be used on patients needing their care.  

The presentation materials cover results obtained for the two above-mentioned projects.  The poster presents material on an algebraic approach to modeling systems with both continuous and discrete behavior.  The framework is based on process algebra, which was developed for discrete systems, and features the development of a tree-based semantic model, called generalized synchronization trees, that uniformly captures a very general notions of time.

Starting from a database of 100’s of real patient electrogram records, we describe how to develop and use a large in-silico cohort consisting of 10,000+ heart models to improve the planning and execution of a clinical trial (CT) for implantable cardioverter defibrillators (ICDs). We illustrate our approach by applying it retrospectively to a real CT that compares two discrimination algorithms (DA) within ICDs for the detection of potentially fatal cardiac arrhythmias. The CT posited that one algorithm would be better than the other but the results of the trial

Start Date: September 1, 2011 The goal of this project is to integrate digital microfluidics systems with thin-film photodetectors in the top plate to realize biochemical target sensing using fluorescence. System control, adaptation, and reconfiguration through software will lead to a general-purpose lab-on-chip computing platform, in the same way as programmable computing devices allow multifunctional capabilities via software on a hardware platform. This level of integration, decision, and controlled reconfigurability will be a significant step forward in clinical diagnostics.