LSU Engineering and Our Lady of the Lake Health Advance AI, Digital Health, and Precision Medicine Across Louisiana

Building “Digital Twins” to Improve Concussion Assessment

LSU Mechanical Engineering Associate Professor Genevieve Palardy is leading a project focused on concussion assessment in football athletes through the creation of personalized “digital twins” of players’ brain mechanics. The team includes Drs. Andrew Becnel, Hunter Gilbert, and Robert Herbert from LSU Mechanical Engineering as well as Dr. Kshitiz Upadhyay from the University of Minnesota.

Working in collaboration with Our Lady of the Lake Health, Palardy’s team engineered custom sensor arrays embedded into helmets, chinstraps, and wearable devices to collect biomechanical impact data during play in real time.

The data is then integrated into computational models, alongside post-game neurological measurements such as EEG and rheoencephalogram data. The long-term goal is to create player-specific return-to-play recommendations grounded in quantitative biomechanical evidence rather than generalized concussion protocols.

“With this project, we’re aiming to establish a protocol and evaluate feasibility for in-game sensing and post-game data collection,” Palardy said. “Combined with brain mechanics simulations, we hope in the long-term to improve understanding and assessment of concussion risk.”

AI Screening for Hidden Heart Valve Disease

Heart valve diseases such as aortic stenosis and mitral regurgitation are common and treatable but often remain undiagnosed — particularly among underserved populations.

LSU Biological Engineering Assistant Professor Bruno V. Rego and collaborators within Our Lady of the Lake Health are developing an AI-powered screening pipeline that analyzes anonymized echocardiograms and electronic health records to identify undiagnosed cases earlier.

The system also examines how social determinants of health may influence referral patterns for minimally invasive cardiac procedures, with the ultimate goal of reducing disparities in cardiovascular care across Louisiana.

“Heart valve disease is often treatable, but too many patients are diagnosed only after symptoms become severe,” Rego said. “Our goal is to use advanced statistical modeling and AI to help identify warning signs earlier from data that already exist in the health system, while also understanding how access to care differs across communities in Louisiana. The goal is not to replace clinical judgment, but to give clinicians better tools. AI can help sift through large amounts of health-record data to flag patients who may need closer evaluation, especially in communities where disease is more likely to go undetected or untreated.”

Using AI to Prevent Childhood Obesity

Louisiana continues to face some of the nation’s highest childhood obesity rates, driven in part by unequal access to healthy food environments, parks, and safe recreational spaces.

To address the issue, LSU Kinesiology Professor Senlin Chen and co-principal investigator LSU Computer Science Associate Professor David Shepherd are developing ProudMe — short for Preventing Obesity Using Digital-assisted Movement and Eating — an AI-assisted mobile health platform designed to help adolescents build healthier habits.

The project, conducted in partnership with Our Lady of the Lake Children’s Health, combines personalized coaching, behavioral recommendations, and statewide GIS analysis of food access and walkability patterns. A pilot summer camp trial was completed in 2025, with a larger randomized trial planned for 2026.

"Part of what makes ProudMe different is the deep integration of expertise from two fields,” Shepherd said. “We met weekly for several months to collaboratively design a digital solution based on my human-computer interaction expertise and his knowledge of behavior change and obesity studies."

Personalizing Hypertension Treatment for Diabetes Patients

Nearly 85% of patients with Type 2 diabetes also suffer from hypertension, yet treatment strategies are often not tailored to individual metabolic profiles.

LSU Electrical and Computer Engineering Chair Shuangqing Wei is working with Our Lady of the Lake Health to develop an AI-driven clinical decision-support system capable of recommending personalized blood pressure medications and dosage adjustments.

Using large anonymized electronic health record datasets, the project applies information-theoretic AI methods to identify treatment strategies based on laboratory results, medications, demographics, and other patient-specific variables. Model development and validation are underway at Pennington Biomedical Research Center.

“Every patient is different, and healthcare decisions should reflect those differences. By applying AI to real-world health data, we are working to give physicians better tools to personalize treatment plans and improve the lives of patients living with both diabetes and hypertension."

AI-Guided Cancer Surgery for Pancreatic Tumors

Pancreatic adenocarcinoma remains one of the deadliest cancers, with five-year survival rates below 10%. Successful surgery depends heavily on removing all cancerous tissue during the initial operation.

LSU Computer Science Associate Professor Jian Zhang is collaborating with Our Lady of the Lake Health to develop an AI-enabled Raman spectroscopy system capable of identifying cancerous tissue in real time during surgery.

The handheld device uses convolutional neural networks to analyze tissue signatures within seconds, helping surgeons continuously assess tumor margins during pancreatic resections instead of relying solely on traditional frozen section analysis, which can take up to 30 minutes per biopsy.

Earlier laboratory studies demonstrated greater than 95% sensitivity and specificity. The current project focuses on validating the technology in real surgical environments using patient tissue samples collected during operations at Our Lady of the Lake.

“By helping surgeons see beyond the visible, AI is transforming the fight against cancer,” Zhang said.

Expanding Human Performance and Safety Monitoring

Additional LSU innovation efforts are also advancing wearable AI technologies for occupational and athletic safety.

Through LSU’s Provost’s Fund for Innovation in Research, LSU Biological Engineering faculty Todd Monroe and Nick Totaro are developing Smartective, a wearable AI platform designed to monitor cognitive load, physiological stress, and environmental conditions in real time.

The system combines wearable sensors, mobile applications, and cloud-based AI analytics to predict injury and accident risk in high-stakes environments such as petrochemical facilities, military operations, and competitive athletics.

Researchers envision future clinical validation and broader deployment across industrial and healthcare settings.

“By combining wearable biosensing technologies, cognitive assessments, and AI-driven analytics, we aim to provide workers, athletes, and military personnel with actionable insights that improve performance while reducing safety risks,” Monroe said. “The project has also strengthened collaborations between LSU and Our Lady of the Lake Health, including our participation in LSU’s Institute for the Health & Performance of Champions, creating new opportunities to translate research discoveries into real-world impact.