FALL 2024 | 13 patients who could benefit from noninvasive monitoring. Part of that process is developing analytics that can translate data in a user-friendly way. The team is assessing the accuracy of existing devices and developing predictive models to translate reactive data into something actionable. The data could be used to show how athletes are performing over time, how they compare to their position groups and how they are performing in relation to the rest of their teammates, Seshadri said. He also is in the early stages of designing his own wearable device for applications ranging from sports medicine to neuromuscular disease, cardiology and neonatal monitoring. Data-Informed Sports When Seshadri came to Lehigh last year, he continued his research into wearable technology and its health implications, which he started during his graduate training at Case Western Reserve University in Cleveland. Seshadri and his students have been working with the men’s and women’s soccer teams, men’s and women’s basketball teams, men’s and women’s swim teams and football. Seshadri’s group collected data from nearly 200 student-athletes last season and will collect data from even more this academic year. Joseph Amitrano ’23, a Ph.D. student studying bioengineering in the Seshadri Lab, is using programs such as Python and RStudio to develop machine learning models that assess the workload-response variables in athletes to evaluate performance and rehabilitation. “We are looking at trends in the data to see if they may be more susceptible to injury, so on that front we are interested in incorporating their sleep parameters, knowing how stressed they are, their energy levels and, from a physiological standpoint, what their heart rate is, how fast they are moving and what their muscle oxygen saturation levels are,” Amitrano said.
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