Carolyn Beck’s research has focused on developing mathematical models that describe a person’s response to anesthesia or other surgical stimuli. These models could then be used to design a partially automated anesthesia delivery process.
For nearly 15 years, ISE Professor Carolyn Beck’s research has been looking at the anesthesia control problem: how to optimize the amount of anesthesia a person receives in surgery.
Her latest project is in the early stages of developing a product that could wirelessly capture a patient’s vital signs and save hospitals time and money while reducing patient risk.
Beck’s research has focused on developing mathematical models that describe a person’s response to anesthesia or other surgical stimuli. These models could then be used to design a partially automated anesthesia delivery process.
“What we’re really trying to do when we do modeling and control with anesthesia is…to optimize or minimize the amount of anesthesia a person gets in surgery,” Beck says.
Existing mathematical models describe how a single input (such as the dosage of one drug) can affect a single output (a vital sign such as blood pressure). But when undergoing surgical operations, people are often treated with multiple drugs at once, which can combine either constructively or destructively and affect multiple vital signs.
The challenge is to develop multi-input, multi-output models that effectively capture all data so it can be used to design an automated system.
But developing an effective system for anesthesia involves factors beyond technology
“In surgery, the surgeon and the anesthesiologist are communicating,” Beck says. “The surgeon will say: ‘I’m going to start the incision now,’ and the anesthesiologist knows something in advance. Then she might turn up the anesthesia just prior to that so the person doesn’t go into shock.”
This is called a feedforward system — one that is based on previous knowledge. Most automated systems are feedback systems, which respond to an output.
The question, then, is how to involve a person — in this case, the anesthesiologist — in an automated, feedforward control design.
“This is something that the airplane industry has dealt with for years,” Beck says. “The autopilot versus the pilot in the cockpit, and how do you go back and forth? How do you make sure when you go from the automated to the actual pilot, the person has the information they need to transition?”
Currently, her research is analyzing how to solve this unique human-machine interface issue.
“We don’t want to take the anesthesiologist out of the operating room,” she says. “So at this point what we’re looking at is, how do you go from a feedback only control design to one that incorporates feedforward information and uses the human in the loop?”
Most recently, Beck’s research has also evolved into an idea for product development that incorporates her knowledge on vital sign outputs.
She has been working with a nurse anesthetist at OSF Saint Francis Medical Center in Peoria, Illinois, who has helped Beck generate a model system that can capture a patient’s vital signs wirelessly so they can be displayed on something like an electronic tablet.
But deciding which vital signs should be captured and how they can be captured using wireless sensors has been a significant part of the problem.
“If we did want to implement something like this, how would we do it?” Beck asks. “If we had the sensors, would they talk to something that the patient wore on their wrist, and then that could be enabled to display on a tablet? Or would it just talk directly to the tablet? Or would it talk to a cloud-based system internal to the hospital?”
Beck says this is an important problem to look at because of the complications involved with measuring a patient’s vital signs.
When patients are in an operating room, they are connected by wireline to various instruments that capture vital signs. When a patient moves from the operating room to recovery, they have to be unhooked from the permanent monitoring units, hooked up to a portable monitoring unit, and then transported to another room where they are then connected to another set of permanent monitoring units.
“There’s a lot of time and confusion involved, frequently, in reconnecting and disconnecting,” Beck says. “It can take anywhere from five to twelve minutes, roughly, depending on the efficiency of the technician doing it.”
According to OSF St. Francis Medical Center, each minute could cost up to $200. Additionally, if the patient is reconnected to the monitoring unit incorrectly, valuable information could be lost and the patient could be at risk.
“If there was a wireless device that all you would have to do is turn the tablet on to get the information — then this would save both time and money and would be safer,” Beck says.
Beck says her research, involving this new product development, has provided both long-term and short-term benefits.
In the short term, she hopes to be able to design a system that will reduce the amount of anesthesia people receive in surgery, but her work in modeling and control design for these systems can also serve as a test case for other problems.
“One of the nice things about the anesthesia studies . . . (is) it can be viewed as sort of a test case for modeling and controlling drugs,” she says. “A surgery is typically anywhere from maybe two to eight hours, which is a short time frame for a drugs control study. If you’re looking at trying to understand chemotherapy and optimizing dosage, these are multi-year processes. So it’s sort of a test case for applying modeling and control techniques to drugs.”