Published:
Author: Jonathan Deutschman
“Getting these images to the doctors early buys them extra minutes, which can make all the difference to patients”—Lidia Al-Zogbi, doctoral student. Photo by Will Kirk.
“Getting these images to the doctors early buys them extra minutes, which can make all the difference to patients”—Lidia Al-Zogbi, doctoral student. Photo by Will Kirk.

EMTs arrive at the scene of a car crash to find two drivers unconscious but breathing. One, bleeding profusely, is stabilized on site and rushed to the ER, where he is treated and eventually released. The other driver appears unhurt, with just a few visible bumps and bruises, but dies on the way to the hospital—the victim of uncontrolled, undetected internal bleeding. 

According to Lidia Al-Zogbi, such a scenario is common but preventable.  

“A significant percentage of pre-hospital trauma deaths are classified as potentially survivable, with the primary cause being uncontrolled internal bleeding, called hemorrhages,” said Al-Zogbi, a fifth-year doctoral student of mechanical engineering in Axel Krieger’s IMERSE (Intelligent Medical Robotic Systems and Equipment) Lab. “There is a concept known as the ‘Golden Hour’—the critical 60-minute window after a traumatic injury occurs. If patients are not stabilized within that timeframe, their chances of survival decrease dramatically.” 

To help improve those odds, Al-Zogbi is working on an autonomous robotic system capable of autonomously initiating diagnostics and performing life-saving interventional procedures to stabilize patients suffering from hemorrhagic emergencies during transport to the emergency department. 

“Our approach bridges the gap,” she said. “This will help ensure that patients make it to the hospital, where doctors alerted to their condition are waiting.” 

Ultrasound imaging is a critical factor in helping emergency personnel identify hemorrhages early, Al-Zogbi said. Though typically tethered to a hospital or office workstation, the technology can be mobilized, wirelessly connecting to an iPad or other tablet. Even so, few EMTs and other first responders have the training or equipment to use ultrasound technology in the field or aboard an ambulance. As a result, by the time the patient arrives at the hospital and imaging can take place, it may be too late. 

“That’s why we’re trying to integrate robotics and artificial intelligence solutions early on,” Al-Zogbi said. 

Al-Zogbi’s robot is programmed to initiate a FAST (Focused Assessment with Sonography in Trauma) Scan via ultrasound, which can alert doctors to hemorrhages while the patient is still en route. If a hemorrhage is detected, the robot can insert an intra-arterial balloon catheter, which can temporarily stem the bleeding until the patient reaches the medical center and a surgeon can take over. This innovative approach can be lifesaving, as it gives clinicians valuable extra time to analyze and assess ultrasound images so they are ready to treat the patient effectively once they arrive.  

“Getting these images to the doctors early buys them extra minutes, which can make all the difference to patients,” Al-Zogbi said.