The unique synergy between CSUN and the medical device company Medtronic Diabetes, located on the northernmost edge of the campus, regularly finds expression in research collaborations, internships and scholarships. Most recently, it has been manifest in research grants that the company (also known as Medtronic MiniMed) awarded to five CECS faculty members to fund one-year projects relevant to diverse aspects of diabetes and the company’s signature insulin pumps. All projects are involving students as integral members of the research team.

bavarianbehzad07.jpgTesting polymers to coat implantable sensors. Implanting sensors under the skin to measure blood glucose on a continuing basis has the potential to simplify insulin regulation in diabetic patients, especially when paired with an insulin pump. But the technology is currently less than ideal because while the insulin pumps last five to eight years, the sensors, exposed to body fluids, degrade and have to be replaced every few months, which is expensive, inconvenient and painful. Behzad Bavarian, professor of manufacturing systems engineering and management, has received a grant to characterize and test different polymers to determine their suitability as coatings to protect the sensors and their compatibility with the human body.

Developing performance models of multi-device body area networks and body area to off-body networks.
DSCN1072.jpgSomeday, in the not-too-distant future, medical devices will use wireless technology to “talk” to each other and monitor such things as blood glucose levels in diabetic patients. Before that scenario can become commonplace, however, developers will need to characterize a complex set of variables relating to sensor placement on the body and how the dynamics of movement, activity levels, stature, body contours and position affect data transmission between devices on and off the body. Electrical and computer engineering professors Sharlene Katz, James Flynn and David Schwartz have received funding to develop a model of transmission and absorption patterns for the radio waves that will transmit the data wirelessly. “Placing wireless sensors on bodies is a brand-new field,” says Katz. “There’s very little information on it. Wherever you put sensors—on an ankle, for instance—parts of the body may block signal transmission between devices. It’s a very complex problem.” The team is aiming to develop a set of guidelines for sensor placement, and the model they create may eventually allow Medtronic’s engineers to design systems that can reliably monitor the blood glucose levels of children, for example, and alert a school- or home-based system when there is a problem that needs attention.

Factoring patient activity into insulin dosage. linCT.jpgUp to now, the medical device industry has relied on a model for insulin dosage that is predicated on a person’s dietary intake. P1010948.jpgIf a patient monitors his or her current sugar level and anticipates having a large meal, for instance, based on that information, he or she will need to inject a certain amount of insulin. What is lacking in this model, however, is consideration of the patient’s physical activity throughout the day. A highly athletic person’s energy expenditure, for example, isn’t factored into the calculations, even though that activity is fueled by sugars in the body, and that person would consequently need less insulin. Mechanical engineering professor C.T. Lin’s project is seeking to develop a mathematical model for measuring and incorporating patientP1010956.jpg activity into the equation for insulin dosage, based on information from sensors that patients could wear to determine how much energy has been consumed. While the initial phase of the project is a feasibility study, if it is successful, it could eventually lead to smarter insulin pumps and more accurate insulin dosing. Graduate students Allen Mekhtarian and Craig Euler are assisting Lin with the project.

MallardBen.jpgDeveloping a feedback system to alleviate pressure on patients’ soles. As diabetes progresses, one of the more common—and unfortunate—effects that patients may experience is the development of ulcers on the bottoms of their feet. In time, nerves may be choked off and die, leading to neuropathy; bones may become brittle, and patients’ arches may fall. Because they lack feeling in their soles, patients may not be aware of the problems, and many no longer walk with normal heel-to-toe flexion; the entire bottom of the foot hits the ground at the same time instead. Aksone Neuvong, D.P.M., at Olive View–UCLA Medical Center has been seeking a feedback system for diabetic patients that uses mapping information from the bottoms of their feet to determine pressure points and then stimulates nerves and leg muscles to change their gait, taking pressure off the sore spots and restoring normal flexion. Ben Mallard, a lecturer in electrical and computer engineering, is working with graduate students to create an interface between the commercial mapping unit and the nascent CSUN feedback system using Bluetooth protocol. “The patients will have electrodes in their socks or stockings, with sensors placed directly on the skin or proximal to the stimulation point for muscle and passive stimulation,” explains Mallard. “As they walk, the system will automatically stimulate the muscles to change their gait and deflect the pressure.” If successful, the project may also be applicable to other conditions that cause disability.

georgewang07.jpgIntegrating diabetes databases. As the amount of information proliferates, it becomes increasingly challenging to compile and mine relevant data. A team led by computer science professor George Wang is laying the groundwork for integrating multiple diabetes-related databases in ways that can benefit clinicians and patients (as well as Medtronic researchers). Under Wang’s direction, a student team made up of graduate student Justin Peckner and senior Ian Maxon, both in computer science, and Kevork Sepetci, an undergraduate in computer engineering, will create a prototype for a comprehensive diabetes database that synthesizes information from internal and external sources, providing “one-stop shopping” for anyone seeking data about diabetes.