Of the many perils facing members of the military, injuries incurred in training or on deployment repeatedly sideline elite operators.

“It’s a pervasive problem,” says Dhruv Seshadri, an assistant professor of bioengineering in Lehigh University’s P.C. Rossin College of Engineering and Applied Science. “We’re looking at how we can integrate physiological data, biomechanical data, and subjective assessments to help reduce the risk of these injuries happening in the first place, and when they do happen, how we can use those data to accelerate the soldier’s return to operation.” 

Seshadri is part of a collaborative, interdisciplinary team that recently received funding from Lehigh University to mitigate musculoskeletal injuries in the military population. Seshadri will work in tandem with Robert Kaleal, director of performance at Spire Academy in Ohio and CEO of Bodies Done Right, and with the FBI and its new recruits to the bureau’s Hostage Rescue Team (HRT). 

The recruits endure a rigorous 10-month training period at the New Operator Training School (NOTS) in Quantico, Virginia. The training involves intense physical challenges, with the operators wearing smartwatches and sweat patches that monitor the effects of these demanding exercises. 

However, the FBI isn’t currently using the data for performance optimization, says Seshadri.

“We plan to monitor the operators using a suite of wearable sensors that will also measure heart rate, respiratory rate, body temperature, heart rate variability, muscle oxygen saturation, and total hemoglobin levels,” he says. “We’ll combine those daily data with subjective assessments that we’ll get when we go to Quantico at discrete time points during the project. We’ll analyze the data, and develop algorithms that we’ll pass on to our partners at Spire Academy and Bodies Done Right, who will develop individualized training plans for each operator based on those algorithms.”

Seshadri and his team will analyze each operator’s day-to-day data based on the context within which they’re performing at any given time—navigating an obstacle course, swimming, rappelling from helicopters, and so on. They’ll compare those to other data points collected from that individual, as well as to information gathered from other individuals within the program.

“Take heart rate variability, for example. We can look at how hard someone is working from a cardiovascular adaptation standpoint, and we can see how that fluctuates over time. We can also examine how that compares to other NOTs who are doing the same activities.”

The researchers will also examine whether the physiological data correlates with errors in decision-making made during training sessions. The data could reveal that illness or injury is preventing the person from performing optimally.

Additionally, the researchers are leading efforts for the FBI HRT team to utilize wearable technology to guide rehabilitation of the operators following injuries such as torn anterior cruciate ligament (ACLs) or torn patellar tendons. Seshadri and Amitrano recently returned from Quantico having used technologies such as the Moxy and Polar devices to assess changes in muscle physiology and cardiac deconditioning in operators currently rehabbing back from significant time-loss injuries.

“We’ll collect the data and integrate it into a green-yellow-red stratification based on severity,” says Seshadri. “We’ll pass that information along to our colleagues at SPIRE and Bodies Done Right who can then prescribe operator-specific workout plans or rehab plans based on science. If the person is healthy, they can focus on training optimization. If the person is injured, having access to the data around an operator’s baseline healthy state will help guide our partners in determining how much and how quickly they should increase that person’s workload so they can return to duty healthy.” 

It’s a truly unique collaboration, he says, one that integrates military performance, sports performance, and bioengineering. The project is also novel in how it treats data, which can oftentimes be so complex that the information is useless to the end user. Seshadri says he and his team did extensive group analysis to determine what their end users—in this case, their colleagues at Spire—want to see in the data and why. 

“We incorporated what we learned and leveraged machine learning and artificial intelligence to distill the data and create predictive trends that are understandable—and actionable.”

For Seshadri, the project represents an opportunity to give back to those serving our country that’s profoundly fulfilling. It’s also an exciting time for the students in his lab.

“It’s really powerful seeing their enthusiasm for this research,” he says. “They’re constantly bringing up new ideas and sharing their data with each other, and it’s that kind of collaborative mindset that fuels creativity, and ultimately, improves outcomes for those people we’re trying to help.”