By Anna Allen, '16
Hilary Briggs, '16, has had her fair share of concussions in the past. She played soccer as a kid and volleyball in high school, two sports where concussions are almost unavoidable. Her frequent experience with concussions inspired her to want to learn more about them.
Despite the common occurrence of concussions, especially among athletes, there is currently no quantifiable way to diagnose them. This issue led Briggs, a mathematical economics major, to join a team of students who spent the summer researching how math could potentially solve this problem.
In an attempt to change the abstract diagnosis process for concussions, Briggs and her teammates, under the guidance of mathematics and computer science professors Kathy Hoke and Joanna Wares, decided to create diagnostic criteria through mathematical modeling. “I was interested in mathematical modeling because it’s math that can really make a difference in the world,” she says. She and her research teammates focused on interpreting the data from a series of balance tests given to patients with concussions, and the process of building a mathematical model for predicting diagnosis of concussions based on those tests.
However, Briggs and her teammates ran into some challenges constructing their mathematical model due to the complicated nature of raw data. “We made the decision to include in the model what was significant or influential to the results, and what factors were correlated with each other,” she says. “These were both strategies that had been used in the past — but never together.” she says. Mathematically, this makes the model extremely innovative.
Briggs and her research team were able to achieve 74.7% accuracy in predicting a diagnosis of concussion. “If I went to the doctor and wanted to be accurately diagnosed whether or not I had a concussion, I would feel supremely confident if the accuracy was about 75%,” she says. “It’s really good for this level of a model, but it still needs a lot more work. Our research is a preliminary step, part of a bigger goal in determining a model that will use balance testing and other tests in order to more accurately diagnose concussions.”
The team is well on their way to this larger goal. This past September, they were able to share their work, as well as the future goals of their research, at the Howard Hughes Medical Institute Symposium where students present research findings to faculty and peers. “I was able to speak with a lot of people and learn from them, and people were also able to learn from me,” says Briggs.
When Briggs and her teammates were not busy constructing a mathematical model for their data or presenting their research, they were busy learning teamwork. “We had to work together,” she says. “If you’re working on separate pieces that diverge, then you’re not going to get anywhere. So the entire process was really collaborative. It was challenging at times, but also extremely rewarding.”
Briggs will be continuing her research throughout the semester. She is interested in exploring the strategy score on the balance testing data, which calculates how people try to balance, as opposed to how well they balance, and another possible diagnostic criteria for concussions.
However, as much as Briggs loves math, her work is more than numbers and algorithms. “Working on a team and meeting people who are at a really high level in their field, and who are really interested and interesting, is why I love this,” she says.