Transforming medicine, one discovery at a time. From groundbreaking medical devices to transformative new treatments, Hopkins BME researchers are engineering the future of medicine and pushing the boundaries of what’s possible. Here’s a glimpse into our latest findings and insights.
Keep up with all our research discoveries on the Research Hub page.
— PETER JENDRICHOVSKY, lead author and
postdoctoral fellow
How does the brain process all the sounds we hear, from a single musical note to the roar of a concert crowd? Patrick Kanold and colleagues have delved into the brain’s “wiring” for sound and found that it is far more precise and organized than previously thought. Using advanced brain imaging, the team found that our brains actively “connect the dots” between different tones to help us interpret complex sounds like speech and music. The research gives new insight into how our brains decipher the world of sound and may inform future studies on hearing disorders.
Manual palpation, a technique used to feel for abnormalities in tissues, can be inconsistent due to variations in a clinician’s speed and experience. Researchers led by Nitish Thakor developed an automated robotic palpation system that uses a special tactile sensor that mimics human touch and accurately detects different fracture types regardless of scanning speed. In tests, the device identified fractures in a chicken wing model with 99.8% accuracy, showing potential to provide a more reliable and objective way to diagnose conditions in both hard and soft tissues.
IEEE Transactions on Medical Robotics and Bionics | May 2025
Frontotemporal dementia is a devastating illness that is notoriously difficult to diagnose, often mistaken for Alzheimer’s disease in its early stages. A team led by Sri Sarma and Chiadi Onyike has developed a promising new diagnostic tool using routine electroencephalogram (EEG) readings of brain waves. Called the “Sink-Index,” their approach analyzes the brain’s electrical activity in a new way, revealing a unique pattern that accurately distinguishes between patients with frontotemporal dementia, those with Alzheimer’s disease, and healthy controls. This discovery could enable doctors to use use a non-invasive EEG to more accurately diagnose complex forms of dementia and begin treatment sooner.
—LUIS A. SANCHEZ, lead author and BME PhD student
Researchers at the Imaging for Surgery, Therapy and Radiology (I-STAR) Lab developed an innovative method to improve surgical precision using machine learning and ultrasound. Their new framework trains an AI model to accurately identify and track anatomical structures by automatically transferring labels from 3D diagnostic images to live 2D ultrasound scans. When applied to spinal surgery, the method precisely segmented and tracked vertebrae with minimal error, demonstrating its potential as a tool for real-time surgical navigation.
— MEERA BHAT (BS and MSE ’25), student author
Bubble continuous positive airway pressure (bCPAP) is a vital treatment for newborns with respiratory distress, but a simple disconnection in the system can go unnoticed in a busy Neonatal Intensive Care Unit (NICU), leading to dangerous drops in oxygen. To solve this problem, students and faculty mentors in the Undergraduate Design Team Program developed an automated monitoring device that sounds an alarm if the bubbling stops, alerting nurses within seconds. In initial tests, the device detected disconnections in just over four seconds.
What if we could create a highly accurate map of our genes to fight diseases? Using a massive dataset of genetic information, Alexis Battle and her team built “gene coexpression networks” that offer a clear picture of how genes work together to maintain our health and what goes wrong when we get sick. These maps can help scientists begin to pinpoint the genes responsible for diseases like cancer, potentially leading to better diagnostics and personalized treatments.
